Opamp bias currents
Ideal opamps have no current flowing into their inputs. This is not true for real world opamps. The input impedance for these is in the order of Mohm to Tohm (tera-ohms). The current flowing into the opamp will offset the voltages on it's inputs. Usually these currents are in the nA range but that depends on the temperature a lot. If your circuit is going haywire when it heats up and you don't have these biasing resistors, then this is probably the cause.
I didn't find a good derivation of the formulas for biasing resistors. All appnotes just give the ready answer. So here they are.
The above schematic shows the inverting opamp. In and Ip are current sources which symbolize the opamp bias currents. In this case any current flowing into the negative input (In) will offset the voltage on it. We will assume that the current In is the same as Ip (we model this opamp's input impedance as an impedance Rd between the input terminals). We have to find the value of R3 so that the current In = Ip will offset the positive input by the same value. This way the voltage difference between the terminals is net zero and the error caused by the bias currents is minimized.
Uwe == Uin is the input voltage, Uwy == Uout is the output voltage.
First we have to find the relation between the currents. From KCL:
I1 + I2 = In -> I1 = In - I2
Now for the opamp output voltage:
Uout = Ud * A -> Ud = Uout/A
Then we find Ud, the voltage between the opamp inputs. For that we use the superposition principle. It's simple - for each voltage we treat all other sources as zero (Current sources give no currents, voltage sources are clamped to ground). We work out the formula for the value that interests us. Then we sum all the formulas. As an example let's calculate Ud.
First we zero all voltages except Uout, and find Ud:
Ud = Uout * R2/(R1+R2)
Then, zero all sources except Uin and find Ud:
Ud = Uin * R1/(R1+R2)
Then, zero all sources except In and find Ud:
Ud = In * R1R2/(R1+R2)
Similarly for Ip
Ud = - IpR3
This formula has a negative sign because the higher Ip, the smaller Ud.
Now we have to sum all these terms above:
Ud = Uout * R2/(R1+R2) + Uin * R1/(R1+R2) + In * R1R2/(R1+R2) - IpR3
Substitute Ud and reorganize the equation:
-Uout/A - Uout R2/(R1+R2) = Uin R1/(R1+R2) + In R1R2/(R1+R2) - IpR3 -Uout(1/A + R2/(R1+R2)) = Uin R1/(R1+R2) + In R1R2/(R1+R2) - IpR3
We want our opamp to output 0V when the input is 0V. Therefore we assume these values for Uin and Uout and see how the math works out:
Uin = 0, Uout = 0 -> 0 = In R1R2/(R1+R2) - IpR3
At the beginning we assumed that In is practically the same as Ip. Therefore we can cancel them out
In ~= Ip R3 = R1R2/(R1+R2)
This is the value of R3 we are looking for.
The non-inverting opamp is depicted on the schematic above. In a similar fashion we depict the bias currents as current sources to ground. The input impedance of the opamp is modeled as an impedance Rd.
In a similar way we start our derivation from the basic opamp equation:
Uout = A * Ud -> Ud = Uout / A Ud = Up - Un
Where Up is voltage at (+) and Um is voltage at (-). We can now express the voltage Un from the superposition principle, in that circuit there is only two sources: Uin and Ip. The Uin term is simply
Up = Uin
This is because when considering the Uin term, we zero the Ip source. The Ip term is:
Up = Ip*R3
Summing these two terms we arrive at Up expression:
Up = Uin + IpR3
Now for the Un calculation. Here we also have just two sources, Uout and In:
Un = Uout * R1/(R1+R2) + In * R1R2/(R1+R2)
Then we substitute Up and Un into Ud expression:
Ud = Uout/A = Uin + IpR3 - Uout * R1/(R1+R2) - In * R1R2/(R1+R2)
We could reorder the expression to have Uout terms on the left hand side, but there is no need as we're going to get rid of them anyway the same way like for the inverting amplifier. We want to pick R3 so that the output voltage is zero when the input voltage is zero. Therefore we just assume that is the case and see how the math works out:
Uin = 0, Uout = 0 0 = IpR3 - In R1R2/(R1+R2) IpR3 = In R1R2/(R1+R2)
Similarly to the previous case we assume that In ~= Ip, because that is how we model the opamp input impedance:
R3 = R1R2/(R1+R2)
Which means that R3, again, should be the same as values of R1 and R2 in paralell.
In both cases we arrived at the same formula for the biasing resistor value. Is it a coincidence? No. In fact, these two circuits are inherently similar from the bias current point of view.
The bias currents are not "concerned" whether they flow into the ground, the source of the input voltage or any other voltage source. Therefore from their point of view we could draw the same symbols for ground, Uin and Uout.
Both of these circuits are special cases of the differential amplifier circuit.
Original notes: File:Opabias.pdf
Analog Devices [MT-038 application note]


Pips in forex
The concept of Pips in forex is very important to understand Forex. Pip tells us the exchange value of two currencies. It is the unit which measures what is the exchange value of the currencies you are trading.
For example, you are trading with GBP/USD and the movement goes from 1.5201 to 1.5202, then the .0001 USD rise is the 1 pip. Most pips are 4 decimal places and they are the last place of the decimal quotation. Except for Japanese Yen pair, they have 2 decimal place.
There is also a fractional pip, it is also known as a pipette. It is pip when the last of the decimal are placed in 3 or 5 decimal places. Like 1.51002 to 1.51003, the last decimal is put on the 5 place, it is one pipette.
How to find out a Pip value
For example, imagine that you are trading on forex market with you 300,000 dollars. The trade is USD/CAD which closes by gaining 20 pips when it reaches 1.0568. To calculate whether you have made profit or loss, we have to follow these steps.
First, we have to multiply the amount of trade by 1 pip to find the number of CAD for each pip. Here, the amount is 300,00 USD and the 1 pip is .0001
So, the multiplication is
300,000*.001=30 CAD per Pip
Second, use the closing rate, here it is 1.0568, to divide the answer to find the USD per Pip.
So, the calculation 30/1.0568=28.39 USD per Pip
Lastly, just multiply the amount of the pips you have gained from the trade, your pips is 20 at this trade of 300,00 dollars, and multiply it with the amount USD per Pip.
The answer to your loss or profit is 20*28.39= 567.80 USD profit.
The answer is in us dollar because you are buying the dollar and selling Pound, that is the answer. Your profit in the dollar when you sell the pound.
Remember, the amount of pips, that your trade has gained will be used in the last step to find out your loss or profit. That is why, if your pip movement is negative, no matter how much the amount it is, it will be a negative result in the profit calculation and you will lose money. So, the most important part of your forex trading is your Pip movement or Pip changing. If pip changes to smaller digit when it was closed then opened, for example, 1.5217 to 1.5211, your pip change is negative, and you will lose money.


Matthew Sottile, PhD (Computer Engineering)
My research work tends to fall somewhere at the intersection of high performance computing, programming languages, and computational science (specifically, computational physics and biology).
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Previously, I taught computer science at the University of Oregon for a couple of years. I taught operating systems, distributed systems, functional programming, and scientific programming courses. Before my excursion into academia, I was a staff scientist at the Los Alamos National Laboratory working on research in high performance computer systems software, applied mathematics, and computational physics. I was a member of both the Advanced Computing Laboratory and the Continuum Dynamics groups at LANL. My PhD research (Univ. of New Mexico, 2006) was focused on the relationship of operating system software to the performance of parallel applications running on large parallel computers. I don’t do much research work in the “systems” (e.g., operating systems, networking, etc…) area of computer science any longer.
Between 2007 and 2009 I worked on a book that was recently published by CRC Press on concurrency and parallelism and how they relate to programming languages. The book is aimed at mid-level undergraduates who may not have had significant exposure to concurrency topics yet.
I’ve written a number of papers and a few open source software packages as well. Check out my page at Google scholar citations to get a look at what papers I’ve written that others have found interesting.


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Kyoka Hashimoto was born in Japan and came to the U.S. when she was five years old. She has always had a love for teaching children and started her education at UC Riverside to pursue her education in Liberal Arts.
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Hi Jim, Thanks a lot for sharing your knowledge through this article. I found it very interesting as you explained somehow difficult concepts in an easy way. Well doneConsequently, even though the second model doesn’t necessarily explain significantly more of the variance, it does include a significant IV and is, therefore, less likely to have biased coefficients. You should ask yourself, does the sign and magnitude of the IV coefficient match theoretical expectations and other research? If so, it looks like the IV is a good addition to the model. Of course, check your residual plots to be sure that you’re not violating any OLS assumptions.Hi Jim, your articles have helped me understand a lot of previous unclear points. A question remains in mind however: I’ve been asked to force the intercept to pass by the zero point inspite of observed data giving a value for the “a” in Y= a+bx. What I noticed is that the residuals do change much for the modified model (Y=bx) . So what is the gain? What consequences are expected? What happens to the p-value? Thank you.
Thank you, Toby! And, I’m very happy you found the blog to be helpful! Happy new year to you too!! This video shows you how to the test the significance of the coefficients (B) in multiple regression analyses using the Data Analysis Toolpak in Excel 2016. For an introduction to multiple.
Let's focus on the three predictors, whether they are statistically significant and, if so, the direction of the relationship. The average class size (acs_k3, b=-2.682) is not significant (p=0.055), but only just so, and the coefficient is negative which would indicate that larger class sizes is related to lower academic performance -- which is what we would expect Thank you for your explanation,Jim.That’s really great! When I’m doing multiple liner regression , I have a question.The liner regression has three independent variables(A,B,C) and one dependent variable(D). I got significant p-value of ANOVA table,but in Coefficients table ,the constant p-value is 0.237,which is not significant ,with one predictor(Variable A) p-value is 0.211,another two predictors have good significant value(P=0.000). In that case ,how can I interpret the results? The hypothesis of the two predictors (variable B and C)which have significant is”there is a relationship between B and D” and “there is a relationship between C and D ” In this case,can I say the two hypothesis were supported? And how can I interpret the one (A)with insignificant p-value in coefficient table? Thank you in advance!
However, I think the more crucial statistic to assess is the p-value for the IV in the second model. That statistic will tell you specifically whether that IV is significant while controlling for all the demographic variables. I think that’s what you really want to know.The standard error (SE) of the coefficient measures the precision of the coefficient estimate. Smaller values represent more precise estimates. Standard errors are the standard deviations of sampling distributions. If you were to perform your study many times, drawing the same sample size, and fitting the same model, you’d obtain a distribution of coefficient estimates. That’s the sampling distribution of a coefficient estimate. The standard error of a coefficient is the standard deviation of that sampling distribution. The SE is used to create confidence intervals for the coefficient estimate, which I find more intuitive to interpret.Thank you for the helpful guide. I was wondering whether the p-value for the dependent value is important and if this also has to be below 0.05 for the null hypothesis to be rejected? p-value in regression coefficient table can be used to drop insignificant variables ; What is feature scaling? Different variables have different magnitude; Feature scaling is done to bring the variables to the same magnitude ; Standardization is one of the methods used for feature scaling ; What is standardization? It is also called normalizatio Can the prologue be the backstory of your main character? Is this wall load bearing? Blueprints and photos attached Reference for the te..
The coefficient value doesn’t indicate the importance a variable, but what about the variable’s p-value? After all, we look for low p-values to help determine whether the variable should be included in the model in the first place.Beta in SPSS refers to standardized independent variables. If that’s the case for your model, then you must use a different interpretation for these coefficients. Standardized coefficients represent the mean change in the DV given a one standard deviation change in the IV. I talk about why you might use standardized values in this post about identifying the most important variables in your model.The other option is to use effect coding (1/-1) instead of dummy coding (1/0). It will allow each first-order effect to be at the mean of the other, aka, a main effect, but the Bs themselves aren’t very interpretable. This is what ANOVA uses.
Lower significance levels (e.g., 0.1) require stronger evidence to determine that an effect is significant. The tests are less sensitive. They are less likely to detect an effect when one exists. On the good side, false positives are less likely to occur.It is standard practice to use the coefficient p-values to decide whether to include variables in the final model. For the results above, we would consider removing East. Keeping variables that are not statistically significant can reduce the model’s precision.Really really helpful blog, still getting my head multiple regression statistics so nice to find someone who simplifies and is clear. Interpreting the coefficients of Fama-MacBeth regression. Ask Question Asked 2 years, 3 months ago. Active 1 year, 9 months ago. Viewed 4k times 6. 4 $\begingroup$ According to Fama & MacBeth (1973) two-step regression, you start with estimating the beta factors. When applying the Fama-French 3-Factor model, you first run the linear regression Regression analysis is a form of inferential statistics. The p-values help determine whether the relationships that you observe in your sample also exist in the larger population. The p-value for each independent variable tests the null hypothesis that the variable has no correlation with the dependent variable. If there is no correlation, there is no association between the changes in the independent variable and the shifts in the dependent variable. In other words, there is insufficient evidence to conclude that there is effect at the population level.
. These are the values that the procedure estimates from your data. In a regression equation, these values multiply the independent variables.I haven’t seen R used much at all. Perhaps it is in some specialized context. But, you probably don’t need to worry about R.How you define “most important” often depends on your goals and subject area. While statistics can help you identify the most important variables in a regression model, applying subject area expertise to all aspects of statistical analysis is crucial. Real world issues are likely to influence which variable you identify as the most important in a regression model.
In the first chapter of my 1999 book Multiple Regression, I wrote There are two main uses of multiple regression: prediction and causal analysis. In a prediction study, the goal is to develop a formula for making predictions about the dependent variable, based on the observed values of the independent variables.In a causal analysis, the independent variables are regarded as causes of the. A coefficient for a standardized independent variable represent the mean change in the dependent variable given a one standard deviation change in the independent variable. The sign for a standardize variable will match the sign for an un-standardized variable. In your case, the negative sign indicates that as the IV increases the DV tends to decrease–a negative relationship.Hi Karen, am performing linear regression analysis in Eviews and half of my variables are unfortunately with p.value larger than 0.05 , even though i dropped out one variable after detecting a multicollinearity it still doesnt change the p.value of the other variables. My research dealing with the effect of explanatory variables such as : R&D Expenses, Company Size, repeated/new partner in alliances ,Total alliances and some more, on the number of patents per year in the pharma industry.My question is what is the implication in that kind of case? what can i do? this is a case study on 3 companies and the size of the sample is 66 observation . Thank you in advance Nitzan. This page shows an example regression analysis with footnotes explaining the output. These data were collected on 200 high schools students and are scores on various tests, including science, math, reading and social studies (socst).The variable female is a dichotomous variable coded 1 if the student was female and 0 if male.. In the syntax below, the get file command is used to load the data. The question is- when I make the analyse of regression, SPSS shows the results and COEF has some value… When I describe these results on paper- should I define the coeff value as a b or β? Thank you in advance
I may be late to providing a course of action, but I agree with Sagar, cross-validation is probably the best approach, build your model with about 90 percent of your observations and use the model to predict the other 10 percent with and without the intercept, use the model that predicts most accurately , do i need to interpret them? For example, in multiple regression I found age was not significant, do i need to interpret this in the usual way? Significant regression, insignificant correlation. Close. 1. Posted by 10 months ago. Archived. Significant regression, insignificant correlation. In multiple regression the coefficients are related to the corresponding partial correlations (conditioning on all other predictors). Partial correlation is not marginal correlation (ordinary.
This tutorial describes how to interpret or treat insignificant levels of a independent categorical variable in a regression (linear or logistic) model. It is one of the most frequently asked question in predictive modeling. Case Study Suppose you are building a linear (or logistic) regression model Zero mediation indicates that the relationship fully exists through the direct relationship between X and Y. Zero mediation exists when there is no relationship between X and M and/or no relationship between M and Y. For any mediation to exist, both the X/M and the M/Y relationships must be significant.
Sir Thankyou so much for the prompt reslonse. Yes, the first model is significant (P=. 02). However, as you also mentioned there seems to be no increase in the predictive capacity when I add the IV (R square remains almost the same in both models) …is that a negative thing? Yes the p value for the IV in the second model is significant. Thankyou again for all your guidance.Thank you for your explanations on how to Interpret Regression Coefficients for Linear Relationships and p-value. It is very clear appreciate you time to put this together. I have one question I was looking at an example on Estimated standardised OLS beta coefficient data. The results show R squared (%) as 26.2 and F-Value 18.14. Please advise how to interpret this 2 figures. Thank youIn most cases you should NOT force the regression line to go through the origin (y intercept equals zero). The fact that you’re observing changes in the residuals suggests that you should not do this. The best case scenario is that forcing the line to go through does not change the residuals.Great blog with detailed explanation! It helps clear my doubts for p-value. Thank you Jim! and Happy new year! 😀This discrepancy sounds like a form of omitted variable bias. You have to remember that these two analyses are testing different models. Pairwise correlation only assesses two variables at a time while your multiple regression model has at least two independent variables and the dependent variable. The regression model tells you the significance of each IV after accounting for the variance that the other IVs explain. When a model excludes an important variable, it potentially biases the relationships for the variables in the model. Hence, omitted variable bias. For more information, read my post about omitted variable bias. That post tells you more about it along with conditions under which it can occur.
Several questions. Have you checked the residual plots? And, were any of your IVs significant? (I’m not quite clear if you’re saying that they all are not significant.)In the model X + M –> Y, if the effect of X on Y completely disappears and M is statistically significant, M fully mediates X and Y. In other words, there is no direct relationship between X and Y at all. It all works through the mediator.
Thanks for the explanation Sir. I have one basic question on interpretation of Beta Values ( coefficient of independent variables). If the independent variables are categorical/qualitative then how do we interpret?The coefficients in your statistical output are estimates of the actual population parameters. To obtain unbiased coefficient estimates that have the minimum variance, and to be able to trust the p-values, your model must satisfy the seven classical assumptions of OLS linear regression.
Linear Regression is a supervised statistical technique where we try to estimate the dependent variable with a given set of independent variables. We assume the relationship to be linear and our dependent variable must be continuous in nature. In the following diagram we can see that as horsepower increases mileage decreases thus we can think. Let's take a look at how to interpret each regression coefficient. Interpreting the Intercept. The intercept term in a regression table tells us the average expected value for the response variable when all of the predictor variables are equal to zero. In this example, the regression coefficient for the intercept is equal to 48.56.This means that for a student who studied for zero hours. The model for a multiple regression can be described by this equation: y = β 0 + β 1 x 1 + β 2 x 2 +β 3 x 3 + ε. Where y is the dependent variable, x i is the independent variable, and β i is the coefficient for the independent variable. The coefficients can be different from the coefficients you would get if you ran a univariate.
However, if you select a restricted range of predictor values for your sample, both statistics tend to underestimate the importance of that predictor. Conversely, if the sample variability for a predictor is greater than the variability in the population, the statistics tend to overestimate the importance of that predictor. Regression with Categorical Predictor Variables . 1. Overview of regression with categorical predictors • Thus far, we have considered the OLS regression model with continuous predictor and continuous outcome variables. In the regression model, there are no distributional assumptions regarding the shape of X; Thus, it is not . necessar .1|) and having in mind that e^b ≈ 1 + b, increase of one-unit of the independent variable “X”, with coefficient b, then the change for dependent variable “Y” should be equal to (100 × b)? Thank you in advance.
Home Online Help Analysis Interpreting Regression Output Interpreting Regression Output. coefficient, the amount it varies across cases. It can be thought of as a measure of the precision with which the regression coefficient is measured. the coefficients on individual variables may be insignificant when the regression as a whole is. To see these sampling distributions in action for a hypothesis test, read my post about p-values and significance levels.When you standardize the continuous independent variables in your model, the output produces standardized coefficients. Standardization is when you take the original data for each variable, subtract the variable’s mean from each observation and divide by the variable’s standard deviation. The main reason I’m aware of for performing this standardization is to reduce the multicollinearity caused by including polynomials and interaction terms in your model. I write about that in my post about multicollinearity.
I have a question. I have an ANOVA F value of 0.06. Both my variables have negative Beta coefficents with first P=0.02 and the second P=0.07. I understand this means the variables relationship with the dependent is inverse, but is it normal to have a good F value and one variable to be deemed not statistically significant.. So, you have to know which category is the baseline. The output should indicate. If it doesn’t state it explicitly, it’s the category that is not listed in the output or does not have a coefficient value. The associated p-value allows you to determine whether the mean difference between a category and the baseline category is not zero.
Statistical significance plays a pivotal role in statistical hypothesis testing. It is used to determine whether the null hypothesis should be rejected or retained. The null hypothesis is the default assumption that nothing happened or changed. For the null hypothesis to be rejected, an observed result has to be statistically significant, i.e. the observed p-value is less than the pre. The regression line on the graph visually displays the same information. If you move to the right along the x-axis by one meter, the line increases by 106.5 kilograms. Keep in mind that it is only safe to interpret regression results within the observation space of your data. In this case, the height and weight data were collected from middle-school girls and range from 1.3 m to 1.7 m. Consequently, we can’t shift along the line by a full meter for these data.
Hi Kim, thanks so much for your kind words! They made my day! While I don’t have PDFs of the blog posts, in several weeks I’ll releasing an ebook all about regression analysis. If you like the simple and easy to understand approach in my blog posts, you’ll love this book. It should be out in early March 2019!Where to know if Regression coefficient is not significant at 5, but at 10% or viceversa? Hello Sir, I hope my questiona finds you, In some articles Regression coeficients are mentioned to be significant at 5% level and some other predictors significant at 10% level. So, where to know if Regression coefficient is not significant at 5, but at 10%? It should be noted that the regression coefficient of ECT is also negatively insignificant showing the presence of equilibrium in the short run .Therefore it can be concluded that both in the absence [pre economic reform period] and presence [post economic reform period] there is a short run equilibrium Suppose you have a pair of variables, say X and Y, and the correlation coefficient (r) is 0.7. If you perform a simple regression using these two variables, you will obtain an R-squared of 0.49 (49%). We know this because 0.7^2 = 0.49. However, unlike correlation coefficients (r), you can use R-squared when you have more than two variables.Another way to look at it is standardized coefficient, which I also write about in my regression ebook. The standardized effect size is better for comparing the magnitude of effect across different types of IVs. This measure tells you how much the DV changes given a 1 standard deviation change in the DV. Because it’s all on a common standardized scale, you can compare the coefficients.
You are a great teacher Jim. The use of simple languages and expressions fascinated me to your website. Please just a quick one. My case is MRQAP model, do I have to plot residual plots to indicate the fit of the MRQAP model? And if yes, please what are the values to use to compute the residual plots (unstandardised coefficients, standardised coefficients etc). Or are p values and R square enough to indicate the fitness of the MRQAP model.To determine that there is a causal relationship, you typically need to perform a designed experiment rather than an observational study.Hi Jim I am hoping you can help with my statistical question. I am looking to conduct a study with low sample size with one IV and either 3 DV’s or 9 DV’s. What statistical analysis issues may I encounter with the more DV’s I include in my study given the low sample size?We ruled out a couple of the more obvious statistics that can’t assess the importance of variables. Fortunately, there are several statistics that can help us determine which predictor variables are most important in regression models. These statistics might not agree because the manner in which each one defines "most important" is a bit different. • Regression coefficients change drastically when adding or deleting an X variable. • A regression coefficient is negative when theoretically Y should increase with increasing values of that X variable, or the regression coefficient is positive when theoretically Y should decrease with increasing values of that X variable
Hi. I want to find out if simple or multiple regressions can be used to explain effects (as in experimental studies)? Thank you.been reading your posts all night, (morning now).. I can’t stop because it’s like a light bulb keeps going off. Been studying this stuff for weeks, now I finally get it thanks to your post. Thank you:) -Extremely tired data science grad student.
The results of your model don’t show that there is relationship between your IV and DV. The p-value indicates this because it is higher than any reasonable significance level. Additionally, the CI for the odds ratio (OR) includes one. In short, your results are not statistically significant. Your sample data do not provide strong enough evidence to conclude that this relationship exists in the population. However, keep in mind that, non-significant results do not prove that the effect/relationship doesn’t exist. Just that your sample didn’t provide strong enough evidence to conclude that it exists. It could be that the sample size is too small or there’s too much variability in the data. Or, perhaps you need to include more variables in the model to control for potential confounding variables.Hello Jim. Hello All. I have one question. Specifically, when the dependent variable (e.g. earnings) is expressed on a logarithmic form (and not the independent variables) via mincer equation, does the interpretation of coefficients follow the below rules?Consider two linear models: L1: y = 39.76x + 32.648628 and L2: y = 43.2x + 19.8 Given the fact that both the models perform equally well on the test data set, which one should be preferThere’s really two primary measures of effect size for regression coefficients. The first is the raw regression coefficient. The coefficient tells you how much the DV changes given a 1 unit increase in the IV. Of course, you have to be careful about determining causality. It might just be an association but not causation. I cover causation vs. correlation in detail in my new Introduction to Statistics ebook by the way.If you’re referring to hierarchical regression as the practice of entering independent variables in groups, such as a group of demographic variables followed by a group of variables you’re testing, yes, you interpret them the same. However, there is one caveat. If a group that is entered into the model later has statistically significant IV, it’s possible that the earlier groups without that significant variable can have omitted variable bias.
BUS105-3 Third Try Q When fitting a linear regression, Q In a multiple regression, after executing and deriving an insignificant Global (ANOVA) test, you should then _____. A conduct a t-test for each individual regression coefficient. Q I have a dataset with 330 samples and 27 features for each sample, with a binary class problem for Logistic Regression. According to the rule if ten I need at least 10 events for each feature to be included. Though, I have an imbalanced dataset, with 20% o positive class and 80% of negative class I have a doubt what happens if my X variable coeffcient is -0.647042012003429 and my significance level is 1.70654E-15Regular regression coefficients describe the relationship between each predictor variable and the response. The coefficient value represents the mean change in the response given a one-unit increase in the predictor. Consequently, it’s easy to think that variables with larger coefficients are more important because they represent a larger change in the response.1. The distribution of the error term is intrinsically tied to the sampling distribution of the coefficient estimates. One of the properties of the normal distribution is that any linear function of normally distributed variables is itself normally distributed. Given this property, it’s not difficult to prove mathematically that the assumption of the normality of the error terms implies that the sampling distribution of the coefficient estimates are also normally distributed. Therefore, if the error distribution is nonnormal, so are the sampling distributions. In that case, the hypothesis tests based on them are not valid.
Multiple Regression Analysis with Excel Zhiping Yan November 24, 2016 1849 1 comment Simple regression analysis is commonly used to estimate the relationship between two variables, for example, the relationship between crop yields and rainfalls or the relationship between the taste of bread and oven temperature Insignificant coefficient in prediction Hi all, I have a question about prediction. Linear predictions in Stata (probably in all software) after any regression seem to use all estimated coefficients regardless their statistical significance Significant correlation but insignificant regression. However, you probably don't have enough information to talk about the partial regression coefficients that result from the multiple regression. In other words, you can talk about the predictors as having meaningful independent relationships, but you can't say for certain what their. 1) Your hypothesis was incorrect. I have no way to know about that. But, it’s something you can investigate. 2) Your hypothesis is correct but your regression model has a problem that produces biased coefficients. This problem is causing the analysis to produce a negative coefficient but it’s should be a positive coefficient. There are a number of reasons why this can occur, including confounding variables, overfitting, data mining, and a misspecified model among other possibilities. Be sure to go through the OLS assumptions and see if your model violates any of them. It will probably take some effort to check these potential problems.How you collect and measure your sample can bias the apparent importance of the variables in your sample compared to their true importance in the population.
What a clear, simple, and easy to understand. You saved my time from reading lots of books. It is really helpful. Would it be possible to get them all in Pdf just to print and read when I am out of network THANK YOU SO MUCH Kim. Beta Coefficients. After the evaluation of the F-value and R 2, it is important to evaluate the regression beta coefficients. The beta coefficients can be negative or positive, and have a t-value and significance of the t-value associated with each. The beta coefficient is the degree of change in the outcome variable for every 1-unit of change. When you take out a term that is involved in something higher, like a two-way interaction that is part of a three-way interaction, you actually change the meaning of the higher order term. The sums of squares for each higher-order term is based on comparisons to specific means and represents variation around that mean. Whilst a regression model will test how the dependent variable changes with a change in the levels of an independent variable. However, I feel like I'm missing something as I'm not sure I fully understand what the p-values of single levels of a dependent variable mean, and also what the overall p-value of a dependent variable in ANOVA test means You’ve performed multiple linear regression and have settled on a model which contains several predictor variables that are statistically significant. At this point, it’s common to ask, “Which variable is most important?”
where b 0, b 1, and b 2 are regression coefficients. X 1 and X 2 are regression coefficients defined as: X 1 = 1, if Republican; X 1 = 0, otherwise. X 2 = 1, if Democrat; X 2 = 0, otherwise. The value of the categorical variable that is not represented explicitly by a dummy variable is called the reference group. In this example, the reference. Multiple regression in Minitab's Assistant menu includes a neat analysis. It calculates the increase in R-squared that each variable produces when it is added to a model that already contains all of the other variables.Hey Karen, While building a model, when I add a function or an interaction effect there is an increase in my adjusted R2 value, However the term that I have added is not significant. In this case, can i still have the term or should i omit that term. The constant term in linear regression analysis seems to be such a simple thing. Also known as the y intercept, it is simply the value at which the fitted line crosses the y-axis. While the concept is simple, I've seen a lot of confusion about interpreting the constant. That's not surprising because the value of the constant term is almost.
coefficients and were interpreted as demand curves - the exogenous variable weather affected supply but not demand, rendering this regression an identified demand curve. Estimating an unidentified equation would produce estimates of an arbitrary combination of the supply and demand equation coefficients, and so could be of arbitrary sign Linear Regression deals with modeling a linear relationship between a dependent variable and several explanatory variables. ergo the Coefficient of Determination is an insignificant. If my Pearson correlation test shows that there is a positive relationship between these 2 variables, but my regression test shows that subjective norms and purchase intention are not significant (I have several indepdent variables in multiple regression analysis and “subjective norms” is one of them. In my regression test, “purchase intention” is outcome variable).I do think it’s odd that R-squared is reasonably high but that the overall F-test is not significant. I suspect something odd is going on.
Thanks Jim for your valuable comments and clear answers. I read well the section of (prediction) because I’m interested in practical use of regression analysis. I have data for cost of different medical tests, so I regress cost against number of patients had the test and the price of the test. Although the model fits well but I found the prediction from the coefficients different from the reality. To be more specific: the model tells me that when the price increases by one unit the cost increases by 8495 units holding the number of patients had the test constant, but when I used Excel and increased the price by one unit for each test I found the cost different. Am I wrong?You would interpret it as a null effect. So if you had a coefficient that was b=2.5, but insignificant, you would interpret that as being 0. So you would not worry if, for example, the sign was opposite what you expected. After fitting a regression model, check the residual plots first to be sure that you have unbiased estimates. After that, it’s time to interpret the statistical output. Linear regression analysis can produce a lot of results, which I’ll help you navigate. In this post, I cover interpreting the p-values and coefficients for the independent variables.Thank you very sincerely for your quick response and clear explaination! This is the most helpful site I’ve ever found!
If the p-value for a variable is less than your significance level, your sample data provide enough evidence to reject the null hypothesis for the entire population. Your data favor the hypothesis that there is a non-zero correlation. Changes in the independent variable are associated with changes in the response at the population level. This variable is statistically significant and probably a worthwhile addition to your regression model.The large p-values indicate that your sample data do not indicate there is a relationship between the independent variables and the dependent variables. The low R-squared also indicates that your model explains a small proportion of the variability in the DV around its mean. Both of those suggest weak or non-existent relationship. I’d also suggest that usually a sample size of 200 is not considered small. Although that depends on the complexity of the model and other issues such as the presence of multicollinearity.Following a regression, an IV was found to be significant. When graphing the relationship however, the slope appears to be very close to 0. I am unsure how to interpret this. What would you recommend?You raise a good point. The interpretation that I present, including the portion that you quote, is accurate when your model doesn’t contain a severe problem. However, if your model does contain a severe problem, it can produce unreliable results, which includes the possibility that the coefficients don’t accurately describe the relationship between the independent variables and the dependent variable. The problem isn’t with how to interpret coefficients, but rather with a condition in the model that causes it to produce coefficients that you can’t trust.
Determining the relative importance of the predictors can be difficult. But, you’re in luck! I’ve written a post about that. Identifying the Most Important Variables in a Regression Model. Read that post, and if you still have questions post them there!If I understand your scenario correctly, you’re saying that the relationship between X and Y is significant. Then, you add M to the model, which is not significant. That indicates there is no relationship between M and Y, which would be zero mediation.So it’s not that it’s wrong, but it changes the meaning of the interaction. For that reason, most people recommend leaving those lower-order effects in.
Im a master student, currently developing my thesis on Post-Earnings Announcement Drift (An Euro Stoxx 50 Analysis) between 2012 and 2017. I’ve defined the event window (-20,0,20) and computed the normal returns and market model parameters for each firm in my study(51 companies). However, the Beta parameters of all aren’t statistically significant (p-value > 5%), which makes my study irrelevant, I don’t know if i did my calculations wrong or its how the sample is but i dont think the calculations are wrong since i tested them in both Excel and Eviews. Definition 1: For any coefficient b the Wald statistic is given by the formula. Observation: Since the Wald statistic is approximately normal, by Theorem 1 of Chi-Square Distribution, Wald 2 is approximately chi-square, and, in fact, Wald 2 ~ χ 2 (df) where df = k - k 0 and k = the number of parameters (i.e. the number of coefficients) in the full model and k 0 = the number of parameters in.
I used to be recommended this website through my cousin. I am not certain whether or not this put up is written by way of him as no one else understand suc certan about my difficulty. You are incredible! Thank you! Correlation coefficients are always values between -1 and 1, where -1 shows a perfect, linear negative correlation, and 1 shows a perfect, linear positive correlation.The list below shows what. Interaction Effects in Regression. In regression, an interaction effect exists when the effect of an independent variable on a dependent variable changes, depending on the value(s) of one or more other independent variables. Here, b 3 is a regression coefficient, and X 1 X 2 is the interaction I found your explanation to be very thorough and easy to follow. I have a dilemma and question that I am hoping you can answer. I am expecting a positive sign, and my results show a negative coefficient but statistically significant. Am I right to interpret it as:Your question contains several terms, hierarchical and beta, that mean different things in different settings and software packages.
Chapter 11 Multiple Regression True/False Questions 1. In regression analysis, every time that an insignificant and unimportant variable is added to the regression model, the R 2 decreases. Answer: False Type: Concept Difficulty: Medium 2. The more variables that are added to the regression model, the better the model will fit the data For example, if your goal is to change predictor values in order to change the response, use your expertise to determine which variables are the most feasible to change. There may be variables that are harder, or more expensive, to change. Some variables may be impossible to change. Sometimes a large change in one variable may be more practical than a small change in another variable.The report with the graphs is produced by Multiple Regression in the Assistant menu. You can find this analysis in the Minitab menu: Assistant > Regression > Multiple Regression.
This is the regression for my second model, the model which uses an additional variable - whether the committee had meetings open to the public. Note that when the openmeet variable is included, the coefficient on 'express' falls nearly to zero and becomes insignificant But I am still a bit confused and it would be great if you could give me a hint. If I have a regression model with 4 variables. Two of them do not have a significant coefficient nor do they contribute to the adj.R2 or F / Fsign. So I droped them. Fruther there is one variable which has the greatest explaination power. The last one is insignificant Hi Jim, thank you so much for this post it’s helped a lot! I’m learning this stuff at uni and have come across a question which has completely confused me and wondered if you could help? The question asks to interpret the regression analysis result and its significance of these regression results:
Hi, I know this may seem to be a very simple question, but is there a difference between R and r? Do they stand for the same thing in regression analysis?The significance level is something that the researchers decide before they start the analysis. There are advantages and disadvantages between use higher and lower significance levels. I’ve written about significance levels in the context of hypothesis testing. In summary:The page 284 of Regression Analysis book which was mentioned effect size, statistical significant and practical significant. Could you let us know the difference between statistical significant and practical significant? How many types of effect size in regression analysis? Plotting regression coeﬃcients and other estimates in Stata Ben Jann Institute of Sociology University of Bern firstname.lastname@example.org September 18, 2017 Abstract Graphical presentation of regression results has become increasingly popular in the scientiﬁc literature, as graphs are much easier to read than tables in many cases. In Stata such. I’m assuming the p-value you’re referring is for the F-test of overall significance. Click that link for a post I’ve written about that test specifically. In a nutshell, when that test is significant, it indicates that your model predicts the mean dependent value significantly better than just using the mean of the dependent variable itself. In other words, your model explains the variability of the values around the dependent variable better than just using the mean. While your model has some explanatory power, it doesn’t guarantee that all of the independent variables in your model are individually significant. It assesses the collective effect of all the independent variables. For example, if your overall F-test is significant and then you add another independent variable to the model that has no relationship with the dependent variable, your overall F-test is still likely to be significant.
I write about this exact cases (unexpected coefficient signs) in the section about Theory in my post about model specification. What I’d recommend is checking your residual plots and doing research to see what others have found. What variables did they use? At the very least, you’ll need to have an explanation for why the unexpected sign is correct. Regression is much more than just linear and logistic regression. It includes many techniques for modeling and analyzing several variables. This skill test was designed to test your conceptual and practical knowledge of various regression techniques. A total of 1845 number of people participated in the test. I am sure they all will agree it was. You don’t mention the coding of the factors, but I’m going to guess they’re dummy coded. When they are, and you have an interaction in the model, the values of the “main effects” are not main effects. So for example, Factor 1 B in the first model is the effect of F1 at ANY value of F2. But in the second model, Factor 1 B is the effect of factor 1 ONLY when Factor 2=0.
Regression analysis that uses polynomials to model curvature can make interpreting the results trickier. Unlike a linear relationship, the effect of the independent variable changes based on its value. Looking at the coefficients won’t make the picture any clearer. Instead, graph the data to truly understand the relationship. Expert knowledge of the study area can also help you make sense of the results.Copyright © 2008-2020 The Analysis Factor, LLC. All rights reserved. 877-272-8096 Contact Us However, all the coefficients become insignificant. How can I interpret these results? And are the one step (with robust standard errors) estimates also robust to heteroskedasticity (across time and countries) You bet they can! The coefficients describe the effects and the p-values determine whether the effects are statistically significant.I would like to consult you on the conflict results that Pearson correlation and Multiple Regression test produce.


Maths is studied throughout the school, following the National Curriculum.
At West Cornforth Primary School, we value every pupil and the contribution they have to make. As a result, we aim to ensure that every child achieves success and that all are enabled to develop their skills. Mathematics is both a key skill within school, and a life skill to be utilised throughout every person’s day to day experiences.
- To foster a positive attitude to mathematics as an interesting and attractive part of the curriculum.
- To develop the ability to think clearly and logically, with confidence, flexibility and independence of thought.
- To develop a deeper understanding of mathematics through a process of enquiry and investigation.
- To develop an understanding of the connectivity of patterns and relationships within mathematics.
- To develop the ability to apply knowledge, skills and ideas in real life contexts outside the classroom and become aware of the uses of mathematics in the wider world.
- To develop the ability to use mathematics as a means of communicating ideas.
- To develop an ability and inclination to work both alone and cooperatively to solve mathematical problems.
- To develop personal qualities such as perseverance, independent thinking, cooperation and self-confidence through a sense of achievement and success.
- To develop an appreciation of the creative aspects of mathematics and an awareness of its aesthetic appeal
Mathematics equips pupils with the uniquely powerful set of tools to understand and change the world. These tools include logical reasoning, problem solving skills and the ability to think in abstract ways. Mathematics is important in everyday life. It is integral to all aspects of life, and with this in mind, we endeavour to ensure that children develop a positive and enthusiastic attitude towards mathematics that will stay with them. To provide adequate time for developing mathematics, maths is taught daily and discretely. However, application of skills is linked across the curriculum, where appropriate.
The National Curriculum for mathematics (2014) describes in detail what pupils must learn in each year group. Combined with our Calculation Policy, this ensures continuity, progression and high expectations for attainment in mathematics. It is vital that a positive attitude towards mathematics is encouraged amongst all of our pupils in order to foster confidence and achievement in a skill that is essential in our society. At West Cornforth Primary School, we use the National Curriculum for Mathematics (2014) as the basis of our mathematics programme. We are committed to ensuring that all pupils achieve mastery in the key concepts of mathematics, appropriate for their age group, in order that they make genuine progress and avoid gaps in their understanding that provide barriers to learning as they move through education.
Assessment, problem solving, mathematical thinking, development of teacher subject knowledge and an emphasis on investigation are essential components of our approach to this subject.
At West Cornforth Primary School, a variety of teaching and learning styles are used in maths lessons.
Teachers strive to:
- Build children’s confidence and self-esteem.
- Develop children’s independence.
- Allow all children to experience regular success.
- Contextualise mathematics.
- Use practical approaches to mathematics (models and images).
- Encourage children to select resources independently to help them.
- Challenge children of all abilities.
- Encourage children to enjoy mathematics.
- Develop a child’s understanding of mathematical language.
- Learn from teachers, peers and their own mistakes.
- Allow children to ask questions as well as answer them.
Children show confidence in believing that they will achieve and they are keen to attempt a range of maths problems, demonstrating flexibility and fluidity to move between different contexts and representation in maths. Children demonstrate a quick recall of facts and procedures. Children develop skills in being articulate and able to reason verbally, pictorially and in written form. Children develop the ability to make connections between mathematical topics. Children make measurable progress against National Curriculum objectives. Children are able to apply their knowledge to a range of real-life situations. At West Cornforth Primary School, the impact of our curriculum design will be that pupils will have developed mathematical skills and knowledge that they are able to use confidently in the next stage of their school career and be confident in selecting the methods, strategies and resources they need. Through becoming confident and fluent in mathematics, pupils will also develop a sense of enjoyment for the subject.
Overview of Maths at West Cornforth Primary School
Year 1 Maths Overview
Year 2 Maths Overview
Year 3 Maths Overview
Year 4 Maths Overview
Year 5 Maths Overview
Year 6 Maths Overview
Curriculum Progression Maps
Progression Map 1 Number and Number System
Progression Map 2 – Addition and Subtraction
Progression Map 3 – Multiplication and Division
Progression Map 4 – Fractions Including Decimals
Progression Map 5 – Ratio and Proportion
Progression Map 6 – Algebra
Progression Map 7 – Geometry – Properties of Shapes
Progression Map 8 – Geometry Position, Direction and Movement
Progression Map 9 – Statistics
Progression Map 10 – Measurement
Maths Vocabulary Progression Document
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I just had an idea that I believe could get students excited about math. Have a math party.
This is the premise, get all the math teachers in a school or department together. Have teachers challenge each other to problems in front of the classes, for the whole day, giving students a chance to view what real mathematics is all about. Let them see minds coming together, discussing, trying, failing, solving and triumphing.
The joy of true mathematics needs to be modeled for students so they can learn to appreciate work of the mind. If it catches on and your school understands, you could do it once a month or once a semester.
Allow students to bring problems to challenge the teachers and let the students join in on solving each others problems.
By: Mr. Woodford
I will reflect on ideas and practices I learn through my formative years as a classroom math teacher.


IMSOCIO 2013 summer program started with students, new and returning, participating in a fun and ice-breaking scavenger hunt event to introduce them to the mapping program Mappler. Students downloaded Mappler’s mobile app “MapplerK” to view a mobile map that showed riddles and the area near to the answer of the riddle where a number card was hidden.
The hunt started at eleven and ended around twelve with students being divided into three teams competing to collect the most number cards. However, For the first time there was a tie with two teams collecting respectively seven number cards each so a tie breaker was made which ended with the winning team being given a ten dollar iTunes gift card as the prize. However, when the prizes where given the students surprised all the preceptors by deciding to give the rewards to the youngest members of IMSOCIO.


Odisha Pathani Samanta Mathematics Scholarship Results 2016- PMST exam results to be Announced
The Pathani Samanta Mathematics Scholarship Test Result 2016 is Declared. Every year odisha board conducts pathani samanta scholarship test or PMST for the students. Lakhs of students appears every year in this examination and now they all are waiting for the Pathani Samanta Mathematics Scholarship results 2016.
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Pathani Samanta is an astrologist. He was a great mathematician also so to pay tribute this legend odisha government conducts a scholarship exam for the school students. Students who cleared this examination get scholarship for further studies. Now students are waiting for this year Pathani Samanta Mathematics Scholarship 2016 Results. This PMST exam is one of the important exams for the Scholarship for thr students in Odisha state. All the students can check PMST orissa results by name online.
So here is a good news for the students now they all can check the Pathani Samanta Mathematics Scholarship Result at official website of Odisha government. If you are facing any problem in checking you pathani samanta scholarship 2016 result then you can follow our step wise directions which are given below.
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2 edition of Actuarial tables based on the U.S. life tables, 1979-81 found in the catalog.
Actuarial tables based on the U.S. life tables, 1979-81
Alice H. Wade
by U.S. Dept. of Health and Human Services, Social Security Administration, Office of the Actuary in Baltimore, Md
Written in English
|Statement||by Alice Wade.|
|Series||Actuarial study -- no. 96., SSA pub -- no. 11-11543., Actuarial study (United States. Social Security Administration. Office of the Actuary) -- no. 96., SSA publication -- no. 11-11543.|
|Contributions||United States. Social Security Administration. Office of the Actuary.|
|The Physical Object|
|Pagination||134 p. ;|
|Number of Pages||134|
History of Actuarial Science: Life tables and survival model, part 2 Volume 2 of History of Actuarial Science, Steven Haberman, ISBN , Editors. Get this from a library! Actuarial tables based on the U.S. life tables: [Felicitie C Bell; Alice Wade; United States. Social Security Administration. Office of the Chief Actuary.].
2 mins read time IRS Life Expectancy Tables. Calculating Table H. Commutation Factors Table H IRS Actuarial Tables. If you have seen our basic introductory course on developing commutation functions, you must have wondered what good these tables are, especially if you are not an actuary. Well if you are a tax accountant or a tax lawyer you must be familiar with the commutation tables used by. Actuarial tables elt15 and am92 pdf stat life publication 12 general rule for pensions and annuities publication 12 general rule for pensions and annuities financial modeling with power bi and dax life insurance calculations. Whats people lookup in this blog: Actuarial Tables Pdf; Actuarial Tables Pdf.
I am currently working on a mortality project, and have been asked to build life tables. So far, I have used the Makeham method. However, I have noticed that the adjustment of the raw death rates is not always good for all the ages. I also feel like using the excel solver gives random results which affects life expectancies. Actuarial Life Expectancy Tables - If you are looking for quotes on different types of insurance then we can give you insurance quotes that will help you find what you are looking for.
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Study #96 Actuarial Tables Based on the U.S. Life Tables: ,by Alice Wade (August ) Study #95 Social Security Area Population Projections, ,by 1979-81 book Wade (October ) Study #94 Economic Projections for OASDI Cost and Income Estimates, ,by Stephen C.
Goss, Milton P. Get this from a library. Actuarial tables based on the U.S. life tables, [Alice H Wade; United States. Social Security Administration. Office of the Actuary.]. Actuarial Mathematics and Life-Table Statistics 1st Edition by Eric V. Slud (Author) ISBN Use these actuarial tables for valuing annuities, life estates, remainders and reversions.
Refer to IRS Publications for examples on how to use the tables. Section of the Internal Revenue Code requires the use of a set of actuarial tables for valuing annuities, life estates, remainders, and reversions, for all purposes under Title 26 except for certain purposes stated in the statute or provided.
Actuarial Tables Based on the U. Life Tables: I. Introduction The National Center for Health Statistics (NCHS) prepares, at 10 year intervals, life tables for the death registration states based on a census of population and deaths in a three year period containing the census year.
U.S. Decennial Life Tables forVolume II, State Life Tables, No. 41, South Carolina. February 37 pp. (PHS) February 37. All books are in clear copy here, and all files are secure so don't worry about it.
This site is like a library, you could find million book here by using search box in the header. Actuarial Mathematics and Life-Table Statistics Eric V. Slud Mathematics Department University of Maryland, College Park °c It covers a review of basic accounting concepts, key topics from U.S.
statutory accounting for general insurers, the measurement of the financial health of general insurers, Statement of Actuarial Opinion and federal income taxes for general insurers. Actuarial Tables, Calculators & Modeling Tools Having the right tools within reach helps you complete your everyday actuarial tasks with ease.
The Society of Actuaries (SOA) offers many tables and tools, including mortality tables, calculators and modeling tools on risk topics. rows Actuarial Life Table. Office of the Chief Actuary.
Life Tables. A period life table is. Actuarial Tables Based on the U. Life Tables: I. Introduction The National Center for Health Statistics (NCHS) prepares, at 10 year intervals, life tables for the death registration states based on a census of population and deaths in a three year period containing the census year.
The series of tables began with tables for the period. Fund Tables: extension of the range of rates of interest in the Compound Interest section: omission of Premium Conversion Tables and ofa table of Officc Premiums for Contingcnt Assurances: and inclusion of additional Statistical Tables.
a statement of the International Actuarial Notation. and Tables of Logarithms, Antilogarithms and Reciprocals. Author(s): Wade,A Title(s): Actuarial tables based on the U.S.
life tables: / A. Wade. Country of Publication: United States Publisher: Baltimore, Maryland. abridged life tables have been constructed by reference to a standard table (3). Methodology developed by Greville was used in constructing life tables for – Since a modiﬁed method has been employed (4).
There are also tables for compound interest calculations, selected statistical distributions, and other actuarial calculations.
You should make yourself familiar with these formulae and tables during your exam preparation. If you are working through exam papers sat beforeyou should use the first edition of the Formulae and Tables book. ACTUARIAL TABLES BASED ON THE U.S. LIFE TABLES: Actuarial Study No. by: Felicitie C.
Bell and Alice H. Wade, A.S.A. Actuarial Mathematics and Life-Table Statistics Eric V. Slud Mathematics Department University of Maryland, College Park °c No book at this level can claim to be fully self-contained, but every attempt has been but every attempt has been made to develop the mathematics to ﬂt the actuarial applications as they Size: KB.
Table Illustrative Life-Table, simulated to resemble realistic US (Male) life-table. For details of simulation, see Section below. Age x lx dx x lx dx 0 40. actuarial tables Download actuarial tables or read online books in PDF, EPUB, Tuebl, and Mobi Format.
Click Download or Read Online button to get actuarial tables book now. This site is like a library, Use search box in the widget to get ebook that you want.
time is denoted in older books as nEx and is called the actuarial present value of a life-contingent n-year future payment of 1: A 1 x:n⌉ = nEx = v n npx Even such a simple life-table and interest-related function would seem to re-quire a table in the two integer parameters x, n, but the following expression.1.
Author(s): Wade,Alice H; United States. Social Security Administration. Office of the Actuary. Title(s): Actuarial tables based on the U.S. life tables, / by Alice Wade.DEPARTMENT OF THE TREASURY Internal Revenue Service 26 CFR Parts 1, 20, and 25 [TD ] RIN AX14 Use of Actuarial Tables in Valuing Annuities, Interests for Life or Terms of Years, and Remainder or Reversionary Interests AGENCY: Internal Revenue Service (IRS), Treasury.
ACTION: Final and temporary regulations.


Smart Ideas: Revisited
The mathematics contest is a regional senior high school sporting activity that was begun in the early 1950s. Since then, it has actually been a tradition to use high school pupils the enjoyable, testing, affordable and also rewarding after-school activity. Trainees get workout, practice trouble fixing abilities, establish management high qualities, and also master analytical and also logical issue solving abilities. The mathematics competition is now in its 51st period as well as supplies trainees a range of different styles including a specific skill competition, team sporting activity, and a county-wide competitive competition. Students additionally obtain workout in the kind of playing in the events or participating in the viewer sports at the occasions. Pupils also obtain the possibility to show off their knowledge and abilities on an amateur degree. The math contest was produced as a method for grade school pupils to display their problem addressing and analytical abilities. Now in its 51st season, the competition offers trainees not only a chance to win interesting prizes, yet to gain unique accomplishment medals for the top 3 winners in each occasion. The medals are created to recognize the most effective in grade school while additionally acknowledging the year's victor. There are several styles of the math contest that can be used by primary trainees. Pupils will require to come up with a mathematics problem set to address for an evaluating panel of educators, moms and dads and various other judges. The medals are after that awarded based upon the highest rating and the order of the medals is identified by the starting point winning candidate. The judging panel contains both instructors as well as parents. Mathematics contests are typically broken down right into 2 different parts. The initial is the factor system where pupils are given a certain number of factors for a correct answer. The 2nd is the skill test or Rubik's dice where the trainee will need to solve a cube with a specific pattern by using a specific collection of standard instructions. Several competitions consist of both parts however some just award among both. The objective of the mathematics competition is to provide the child an outstanding rating so they can boost their qualities in maths as they grow older. This is why it is essential to prepare well prior to the event. Parents can help with the research aid because they have access to all the information about the topic. They can learn the analytical method along with the method needed for fixing the challenge. It will certainly assist them find out just how to prepare for the mathematics competition. They can likewise look up the past year's solutions grades and also check out the most effective methods for this year's competitors. This can help them discover exactly how to contend along with recognize what the judges are trying to find. The math contest is easy to sign up for and also simple to send since the internet site is very easy to utilize. They provide very clear guidelines on how to finish the kinds and exactly how to gather the mathematics worksheets. Pupils can likewise discover more about just how they will be rewarded with the mathematics competition outcomes. It is easy to register for the math contest and kids can obtain a prize along with improve on their qualities from the experience.


The school bus set is a great way for children to practice math while tapping into their creativity!
All pieces feature SuperColor® technology on both sides for double the learning. Side one contains all the tiles needed to build the bus. Side two includes numbers 0-9, plus sign, minus sign, greater than/less than sign and equal sign.
The set is compatible with all Magna-Tiles® Structures and original Magna-Tiles® Sets.
This set contains 18 three-inch square tiles and 2 wheeled chassis.
Ages 3 years and up.
While returns are subject to each individual store's return policy, we are happy to help facilitate this process. We do not charge a return fee, and will be happy to schedule a pickup with one of our drivers. There is a $25 minimum in product value required to return an item(s) (multiple products can be combined).
Please check the list below to find the store's individual return policy, and then fill out the returns form. If your store is not listed below, you can still fill out a return form and we will contact the store to try and setup a return!


Maybe if we tell people the brain is an app they'll start using it.
that one is pretty good...but I fear brain usage is down all over
My sentiments exactly, my younger brother teaches maths at secondary school. The other year he showed me two maths books, one was a year 8 book from the 1980's that he used as a kid, another was a current year 10 maths manual. I was shocked, kind of amused, when I saw how much the school education system had dumbed down the material, and that the older Year 8 book was actually more advanced than the one currently in use in Year 10 maths. Well, that's the situation here. Maybe I should have posted this on the Catastrophism thread
Post by themirrorthief on Sept 14, 2018 17:21:50 GMT -5
the love of money is the root of all evil but in heaven there are many mansions and the streets are paved with gold...this sounds confusing but the truth is being pious has its rewards and that is the point the bible is trying to get across.
if people think you are crazy, they'll never suspect how insane you are


More often than not, students who are good at quick sums and arithmetics may struggle to fully comprehend the nature of mathematical problem-solving. When maths problems are articulated with written words and comprehension, some of the foundational concepts students learn about maths get lost in the process.
Solving maths word problems often require us to consciously choose and employ strategies that encourage stronger critical thinking towards the problem at hand. However many students lack the metacognitive abilities required to solve the richer maths problems
Luckily, years of research and testing have led to ordinary students being empowered to solve extraordinary problems. Here is one of the many approaches we utilise to educate our students to solve complex maths problems.
1. Define the problem: Before students solve a problem, they need to know what it’s asking for. Oftentimes, students struggle with word problems as there aren’t specific mathematical operators that outline this clearly for them.
The purpose of this step is to clearly pronounce and identify the common denominators and key operators in the problem. Encourage students to list out the points of what they already know and highlight the parts that they’re unclear on. This will aid them to utilise the right strategies to fill in the gaps. Practically, here is an approach to help students better define and understand the problem.
Identify the important information from the noise:
Example question: Darius is collecting money for a local animal shelter. He starts with $2.50 of his own money, then his friend Boyd gives him $5.00 to contribute for the same cause. How much money has Darius collected for his local animal shelter?
While we can instantly look at the problem without really needing to know the names and the charity scenario as it is a very simple addition problem, students can struggle to determine what’s relevant in the information given to them.
By teaching students to sort and sift relevant information in a problem, they will know to simply add the two given numbers. A good way to practise this is to have students change the names and scenarios to show them that there will be no impact on the result. Then, they’ll realise that the names and scenarios don’t need to be a focal point while solving a problem.
2. Plan the approach: Once you have defined the nature of the problem, identify the strategies that you can use to go about solving this problem. Some strategies that could be employed are:
Guess and check: Students make an educated guess and then apply the answer back into the original problem. If their guess didn’t solve the problem, they now have an answer of what it can’t possibly be.
Visualise the problem: Visualising an abstract problem often makes it easier to solve a problem. Students can simply draw the problem in a way that helps them better understand the core of the problem.
Work backwards: Working backwards is useful if students are tasked with finding an unknown number in a problem or mathematical sentence. For example, Johnny went to an orchard and picked 6 apples. By the end of the day, Johnny came home from the orchard with 10 apples as he was gifted them by his friends. How many apples did Johnny’s friends give him? At the core of the problem, it is simply 6 + x = 10. By working backwards, students can easily solve this by:
Starting with the number 10
Then removing 6 from 10
Leaving them with 4
Then students can check to see if 4 will fit to replace x
3. Do the problem: Now that students have learnt to identify the problem and plan their approach, they work towards solving the problem But by launching into the problem without a targeted approach to keep each step in check, students will risk making silly errors. Here are some ways that we help students execute what they’ve learned:
Document the steps: Model the process of writing down every step taken to complete a problem. This will allow students to keep track of their thoughts, pick up errors and revise their steps before they reach a final solution.
Check, check and check again: Encouraging students to check their work as they go and once they have finished is a crucial strategy, not only in mathematics but across all learning areas. Embed questions such as:
Does that last step look right?
Does this step follow on from the prior step?
Are all the smaller sums in previous steps captured correctly?
Are the steps that I'm taking applicable to prior problems I've solved?
By posing questions like this, students will develop natural diligence toward solving maths problems.
Solving maths problems enhance a student’s ability to process information and to think creatively and critically. Although challenging, by applying various strategies and persevering, students will unlock their capabilities and experience the joys of solving real-life scenarios and objects in their learning. Above all, students with advanced maths problem-solving skills have a greater depth of being able to tackle all styles of problem critically and analytically.


For the poll obsessed here, understanding how different odds makers are coming up with their projections can be difficult. My own model is pretty complicated, and I run about 20,000 election simulations to create it.
But the basic idea is pretty simple: you calculate the odds of winning a state based on the polling, and then you run a bunch of simulations to see what the probably result is. Now there are some flaws in this more basic approach (eg dependent versus independent variables) but the basic principle is simple.
So I created a more simplified model that you can use. If you follow the link below, you can enter your odds for each state, and generate the probability of an Obama victory. Because of limitations with Google docs, this runs only 1,650 or so simulations, but the basic idea is pretty straightforward (and it took only an hour to create).
If you find an bugs send me a message here or at on twitter at dcg1114.
Before anyone asks - I am part of the legal protection team here and will be working over the next week.


In the Philippines, it is only in the past two to three years that Singapore Math has been embraced and used by the country’s top private schools such as Xavier School, Immaculate Conception Academy (ICA), Victory Christian International School, and other premiere learning institutions. Because of this, Singapore Math has earned the reputation of being the best math program in the country, or should we say, the most highly respected math course in the land.
The popularity of Singapore Math hails from the fact that Singaporeans are found to occupy top positions in different examinations and tests conducted around the world in measuring math proficiency. Moreover, Singaporeans have consistently remained in the top spot in the recent years. Educators around the world have recognized this obvious advantage. Americans have in fact used the Singapore Math program in some of their public schools and validated the pronounced improvement of their students in terms of performance in math proficiency tests from the use of Singapore Math as their math curriculum. Even homeschool curriculum providers such as Sonlight Curriculum and other homeschool resource centers such as Rainbow Resource Center have made Singapore Math readily available to homeschooling parents for use on their own children.
There are quite a number of types of Singapore Math books used in Singapore. The most widely used series for preschool levels K1 to K2 (kinder to prep) is the New Earlybird Kindergarten Mathematics series. For the primary levels or elementary levels, the most widely used Singapore Math is the My Pals Are Here series. These are the same math series used by top schools in the Philippines. The publishers have recently released the latest edition (second edition) of My Pals Are Here Math. This Singapore Math series comprises of primary or elementary levels one through six. Levels one through three consist of two textbooks and four workbooks. Levels four through six only have two textbooks and two workbooks but are thicker than the lower grades.
Singapore Math is designed for the student to learn and understand mathematics without memorizing a set of rules. It is arguably the “smart” math and challenges each student to think beyond a simple mathematical concept. It may not be easy nor cheap but after using the books, it truly is bang for every buck.


What May be the Median Math Score inside the Usa?
What will be the median math score in the United states?
If you’ve spent time at a four year college, the bottom line answer is likely that the score isn’t really higher.
The NCET or National Council for Teaching of Mathematics, which administers the NCET tests, publishes scores for the student who took the NCET math test. They do that as soon as every single four years. The fact that the NCET makes use of a multiple-choice format (taken individually) shows how significant it’s for students to succeed around the multiple-choice portion of your test, and how little value the scoring by personal computer is provided.
The NCET test is also referred to as the NCET A number of Option (NCET-MC). The NCET-MC is really a fairly hard math test, but for all those who want to have an understanding of what’s the median math score in the Usa, and what NCET is up against, the NCET-MC is maybe the perfect tool available.
One thing concerning the NCET-MC is that it’s certainly hard, specifically the multiple-choice section. The test taker should know what he or she is doing on that section of your test, simply because it requires mathematical abilities. https://www.cim.edu/ In the identical time, the test taker should be in a position to concentrate, and she or he should really have a sense of humor. Moreover, the test taker should be prepared to take some time off if he or she gets frustrated.
There are quite a few reasons why a lot of students do poorly around the NCET math test. Some students struggle with numbers, though other people just have poor math expertise.
For students that show poor math capabilities, by far the most popular reason for failing the test isn’t recognizing the answers. When the test taker has prepared appropriately, knows what to count on and knows what queries are coming up, the students’ opportunity of passing is a great deal improved.
The NCET-MC math test has two sections, the initial a single requiring the student to answer inquiries. The student is then permitted to resolve for answers. At the finish from the section, the student’s answer is in comparison to the NCET math typical score.
On the NCET math test, students are asked to solve for difficulties, which include “Find the area in the side of a triangle as a result of lowering the height of your side by the length of the side.” And the NCET-MC test has 3 queries that make use of the queries from the far more generally employed section with the NCET-MC test, that is the area and perimeter inquiries.
The last section on the NCET-MC math test needs the student to “solve for answers” on the NCET-MC location and perimeter questions. It is actually needed for students to apply their knowledge of standard algebra and geometry so as to pass the test.
Because countless students don’t understand the unique strategies in which their math skills is often improved, or do not have the expertise to apply them, there is certainly not plenty of motivation to find out. Furthermore, the only teachers that countless students have to function with are these that are available in by means of the Department of Education’s ECLS program, which puts students by means of remedial mathematics.
Many students will go into college with out obtaining discovered the math abilities necessary to succeed. Together with the passage of time, NCET-MC test scores have risen slightly, however they nevertheless don’t have the same regular as those that graduate from major math and science colleges.
If a student is really serious about improving their math expertise, the only solution to achieve that is to take the proper course of action and enroll within a class. There are plenty of programs and teachers which could assistance people who wish to enhance their math skills.


by Jim Woods | April 10, 2009 4:36 am
The investing game is chock-full of esoteric lingo and obscure mathematical and technical analysis models. All too often, the unfamiliar terminology and the complexity of the models leave the neophyte investor perplexed.
I recently received an e-mail from an OptionsZone reader that exemplifies just this state of confusion surrounding one frequently mentioned technical analysis tool.
The reader asked the blunt question: “What the bleep is a Fibonacci?”
To answer this question properly, we have to go all the way back to 13th-century Italy. It was then that a brilliant mathematician named Leonardo Pisano, who was nicknamed “Fibonacci,” identified a sequence of numbers that possessed an unusual relationship.
Here is the famous Fibonacci number sequence: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, etc. The relationship between these seemingly unrelated numbers is that each term in the sequence is simply the sum of the two preceding terms. This relationship persists into mathematical infinity.
The unusual characteristic of this numerical sequence is that each number is approximately 1.618 times greater than the preceding number.
So much for the “what” of the Fibonacci, now we need to know how this sequence of numbers and the relationship between them is applied to an analysis of the financial markets.
Technical analysts use the relationship between every number in the Fibonacci series as the basis for identifying the common ratios used in price retracement studies.
When technical analysts look at price action through the Fibonacci prism, they identify two extreme points (usually a major peak and trough) on a stock chart, and then divide the vertical distance by the key Fibonacci ratios.
And what are those key ratios? They are 23.6%, 38.2%, 50%, 61.8% and 100%. Once these rations are identified, they signify potential areas of support and resistance. The question now is why did the aforementioned ratios become the key ratios?
Well, here is where the Fibonacci ratios become really esoteric. The theory here is that in nature, and in the financial markets, systems will tend to display numerical characteristics that resemble key Fibonacci patterns. Beehives, spiral galaxies, the human anatomy and, yes, the patterns in the equity markets, all display profound and unequivocally non-coincidental Fibonacci patterns.
Applied to the market, this technical tool is used to help identify critical points that cause an asset’s price to reverse. It’s also used to monitor the direction of a prior trend and how likely it is to continue once the price of the asset has retraced to one of the key ratios.
In the chart below provided by the Investopedia Web site, we can see how a Fibonacci retracement is plotted on a stock chart.
Here we see how a stock’s price tends to change direction as it nears key Fibonacci support and resistance levels. The most famous of these ratios is 61.8%, which is also referred to as “the golden ratio” or “the golden mean”.
This ratio is determined by dividing one number in the series by the number that follows it. For example: 8/13 = 0.6153, and 55/89 = 0.6179.
Now I know what you might be thinking right now. Does this Fibonacci thing really work? The answer to that question is yes and no.
Yes, using Fibonacci retracement patterns along with other technical analysis tools can work by giving you the edge when it comes to identifying key resistance and support levels in a stock. But no, relying solely on a Fibonacci retracement pattern or any single technical analysis measurement as the Holy Grail of investing does not work.
So, now that you know what the bleep a Fibonacci is, you can now move on to other simple questions such as the origins of life on earth, the Big Bang and quantum mechanics.
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The golden ratio is an irrational number, approximately 1.618 033 988 749 894 848, that possesses many interesting properties. Shapes defined by the golden ratio have long been considered aesthetically pleasing in Western cultures, reflecting nature's balance between symmetry and asymmetry and the ancient Pythagorean belief that reality is a numerical reality, except that numbers were not units as we define them today, but were expressions of ratios. The golden ratio is still used frequently in art and design. The golden ratio is also referred to as the golden proportion, golden mean, golden section, golden number, divine proportion or sectio divina.
There are two ways to divide Get Things Done into two sections according to the ratio. The first way is to divide it when Mark sings "answerless question" on "Hamlet" and the second way is to divide it is a few seconds after the keyboards come in on "Lucy."


I am a Professor of Mathematics in the Department of Mathematics and Statistics at Auburn University. My primary interests are numerical and computational mathematics: Numerical P.D.E., Numerical Analysis, and Computational Science.
I hold a B.Sc. in Aeronautical Engineering from the Technion – Israel Institute of Technology and a Ph.D. in Mathematics from Carnegie Mellon University. I am currently involved in several research projects (some are interdisciplinary) and serve on five editorial boards; see my Curriculum Vitae
(and the other tabs) for additional information and details.
Those interested in mathematics genealogy can explore my mathematical lineage (at the Mathematics Genealogy Project). For those who care about such things, my Erdös Number is 3 (for information about Erdös numbers see the Erdös Number Project).
Some of these pages are still under construction, eventually they will all be populated and the material from my old web page migrated here.
During the 2014–2015 academic year I am on assignment to the National Science Foundation in the Division of Mathematical Sciences. I am a Program Director (Rotator) in the Computational Mathematics Program.
For additional information see the page About NSF Rotator Positions.
Classes Fall 2014–Spring 2015
Office Hours Fall 2014–Spring 2015
- If you need to get in touch with me, please send me an e-mail.
The views, opinions, and comments on these pages are those of A. J. Meir.
These do not necessarily reflect the position of Auburn University, or the Auburn University Department of Mathematics and Statistics.