normality test spss skewness kurtosis
Any skewness or kurtosis statistic above an absolute value of 2.0 is considered to mean that the distribution is non-normal. Skewness Value is 0.497; SE=0.192 ; Kurtosis = -0.481, SE=0.381 $\endgroup$ – MengZhen Lim Sep 5 '16 at 17:53 1 $\begingroup$ With skewness and kurtosis that close to 0, you'll be fine with the Pearson correlation and the usual inferences from it. The question arises in statistical analysis of deciding how skewed a distribution can be before it is considered a problem. Normality test is intended to determine the distribution of the data in the variable that will be used in research. The histogram shows a very asymmetrical frequency distribution. Skewness, in basic terms, implies off-centre, so does in statistics, it means lack of symmetry.With the help of skewness, one can identify the shape of the distribution of data. Uji Normalitas SPSS dengan Skewness dan Kurtosis. The test is based on the difference between the data's skewness and zero and the data's kurtosis and three. Method 4: Skewness and Kurtosis Test. Under the skewness and kurtosis columns of the Descriptive Statistics table, if the Statistic is less than an absolute value of 2.0 , then researchers can assume normality of the difference scores. A scientist has 1,000 people complete some psychological tests. Jarque and Bera (1987) proposed the test combining both Mardia’s skewness and kurtosis… Alternative Hypothesis: The dataset has a skewness and kurtosis that does not match a normal distribution. normality are generalization of tests for univariate normality. Skewness in SPSS; Skewness - Implications for Data Analysis; Positive (Right) Skewness Example. If the data are not normal, use non-parametric tests. Observation: Related to the above properties is the Jarque-Barre (JB) test for normality which tests the null hypothesis that data from a sample of size n with skewness skew and kurtosis kurt. Skewness and kurtosis statistics are used to assess the normality of a continuous variable's distribution. The normality test helps to determine how likely it is for a random variable underlying the data set to be normally distributed. More specifically, it combines a test of skewness and a test for excess kurtosis into an omnibus skewness-kurtosis test which results in the K 2 statistic. Data that follow a normal distribution perfectly have a kurtosis value of 0. If the data are normal, use parametric tests. Since it IS a test, state a null and alternate hypothesis. as the D'Agostino's K-squared test is a normality test based on moments . median 32.000. std. So, it is important to have formal tests of normality against any alternative. The test rejects the hypothesis of normality when the p-value is less than or equal to 0.05. The Jarque-Bera test uses these two (statistical) properties of the normal distribution, namely: The Normal distribution is symmetric around its mean (skewness = zero) The Normal distribution has kurtosis three, or Excess kurtosis = zero. In the special case of normality, a joint test for the skewness coefﬁcient of 0 and a kurtosis coefﬁcient of 3 can beobtained onconstruction of afour-dimensional long-run … If the values are greater than ± 1.0, then the skewness or kurtosis for the distribution is outside the range of normality, so the distribution cannot be considered normal. Recall that for the normal distribution, the theoretical value of b 2 is 3. The Jarque-Bera test tests the hypotheisis H0 : Data is normal H1 : Data is NOT normal. They are highly variable statistics, though. We can make any type of test more powerful by increasing sample size, but in order to derive the best information from the available data, we use parametric tests whenever possible. Last. For Example 1. based on using the functions SKEW and KURT to calculate the sample skewness and kurtosis values. The steps for interpreting the SPSS output for skewness and kurtosis statistics 1. Assessing Normality: Skewness and Kurtosis. First, download the macro (right click here to download) to your computer under a folder such as c:\Users\johnny\.Second, open a script editor within SPSS In the special case of normality, a joint test for the skewness coefficient of 0 and a kurtosis coefficient of 3 can be obtained on construction of a four-dimensional long-run covariance matrix. Here we use Mardia’s Test. For a sample X 1, X 2, …, X n consisting of 1 × k vectors, define. Positive kurtosis indicates that the data exhibit more extreme outliers than a normal distribution. Negative kurtosis indicates that the data exhibit less extreme outliers than a normal distribution. It is a requirement of many parametric statistical tests – for example, the independent-samples t test – that data is normally distributed. SPSS obtained the same skewness and kurtosis as SAS because the same definition for skewness and kurtosis was used. The normal distribution has a skewness of zero and kurtosis of three. If you need to use skewness and kurtosis values to determine normality, rather the Shapiro-Wilk test, you will find these in our enhanced testing for normality guide. An SPSS macro developed by Dr. Lawrence T. DeCarlo needs to be used. Skewness. While Skewness and Kurtosis quantify the amount of departure from normality, one would want to know if the departure is statistically significant. We have edited this macro to get the skewness and kurtosis only. How to test normality with the Kolmogorov-Smirnov Using SPSS | Data normality test is the first step that must be done before the data is processed based on the models of research, especially if the purpose of the research is inferential. Similar to the SAS output, the first part ofthe output includes univariate skewness and kurtosis and the second part is for the multivariate skewness and kurtosis. You can learn more about our enhanced content on our Features: Overview page. Baseline: Kurtosis value of 0. If the coefficient of kurtosis is larger than 3 then it means that the return distribution is inconsistent with the assumption of normality in other words large magnitude returns occur more frequently than a normal distribution. The d'Agostino-Pearson test a.k.a. (Asghar Ghasemi, and Saleh Zahedias, International Journal of Endocrinology and Metabolism. The importance of the normal distribution for fitting continuous data is well known. The statistical assumption of normality must always be assessed when conducting inferential statistics with continuous outcomes. Final Words Concerning Normality Testing: 1. The SPSS output from the analysis of the ECLS-K data is given below. Skewness. 2. AND MOST IMPORTANTLY: In order to determine normality graphically, we can use the output of a normal Q-Q Plot. Dev 8.066585. mean 31.46000 This quick tutorial will explain how to test whether sample data is normally distributed in the SPSS statistics package. This column tells you the number of cases with . Skewness and kurtosis statistics can help you assess certain kinds of deviations from normality of your data-generating process. D’Agostino Kurtosis Test D’Agostino (1990) describes a normality test based on the kurtosis coefficient, b 2. Z = Skew value , Z = Excess kurtosis SE skewness SE excess kurtosis As the standard errors get smaller when the sample A z-score could be obtained by dividing the skew values or excess kurtosis by their standard errors. kurtosis-0.56892. Use kurtosis to help you initially understand general characteristics about the distribution of your data. SPSS computes SE for the mean, the kurtosis, and the skewness A small value indicates a greater stability or smaller sampling err Measures of the shape of the distribution (measures of the deviation from normality) Kurtosis: a measure of the "peakedness" or "flatness" of a distribution. The frequency of occurrence of large returns in a particular direction is measured by skewness. where tests can be used to make inference about any conjectured coefﬁcients of skewness and kurtosis. The null hypothesis for this test is that the variable is normally distributed. If you perform a normality test, do not ignore the results. The following two tests let us do just that: The Omnibus K-squared test; The Jarque–Bera test; In both tests, we start with the following hypotheses: There are several normality tests such as the Skewness Kurtosis test, the Jarque Bera test, the Shapiro Wilk test, the Kolmogorov-Smirnov test, and the Chen-Shapiro test. Syarat data yang normal adalah nilai Zskew dan Zkurt > + 1,96 (signifikansi 0,05). Normality tests based on Skewness and Kurtosis. The following code shows how to perform this test: jarque.test(data) Jarque-Bera Normality Test data: data JB = 5.7097, p-value = 0.05756 alternative hypothesis: greater The p-value of the test turns out to be 0.05756. For test 5, the test scores have skewness = 2.0. There are a number of different ways to test … The tests are developed for demeaned data, but the statistics have the same limiting distributions when applied to regression residuals. Adapun kurtosis adalah tingkat keruncingan distribusi data. Another way to test for multivariate normality is to check whether the multivariate skewness and kurtosis are consistent with a multivariate normal distribution. 2) Normality test using skewness and kurtosis A z-test is applied for normality test using skewness and kurtosis. 4. For a normal distribution, the value of the kurtosis statistic is zero. Normal Q-Q Plot. A histogram of these scores is shown below. Kurtosis. skewness-0.09922. Jadi data di atas dinyatakan tidak normal karena Zkurt tidak memenuhi persyaratan, baik pada signifikansi 0,05 maupun signifikansi 0,01. We can attempt to determine whether empirical data exhibit a vaguely normal distribution simply by looking at the histogram. Determining if skewness and kurtosis are significantly non-normal. However, in many practical situations data distribution departs from normality. For example, the sample skewness and the sample kurtosis are far away from 0 and 3, respectively, which are nice properties of normal distributions. If it is, the data are obviously non- normal. Pada kesempatan kali ini, akan dibahas pengujian normalitas dengan nilai Skewness dan Kurtosis menggunakan SPSS. A measure of the extent to which there are outliers. Another way to test for normality is to use the Skewness and Kurtosis Test, which determines whether or not the skewness and kurtosis of a variable is consistent with the normal distribution. 3. Hence, a test can be developed to determine if the value of b 2 is significantly different from 3. Skewness secara sederhana dapat didefinisikan sebagai tingkat kemencengan suatu distribusi data. skewness or kurtosis for the distribution is not outside the range of normality, so the distribution can be considered normal. Kurtosis indicates how the tails of a distribution differ from the normal distribution. One group of such tests is based on multivariate skewness and kurtosis (Mardia, 1970, 1974; Srivastava, 1984, 2002). I ran an Anderson darling Normality Test in Minitab and following were the results P-Value 0.927 Mean 31.406 Std.Dev 8.067 Skewness -0.099222 Kurtosis -0.568918 I also Calculated the Values in an Excel sheet and following were the results. Quick tutorial will explain how to test … normality are generalization of tests for univariate normality complete! Kurtosis statistics can help you initially understand general characteristics about the distribution can used... Your data-generating process how likely it is considered to mean that the is! Spss statistics package significantly different from 3 well known normality test spss skewness kurtosis to get the and! Less than or equal to 0.05 departure from normality, one would want know... Kinds of deviations from normality output from the analysis of the ECLS-K data is normal H1: data is known. Above an absolute value of 0 H1: data is normally distributed pada kesempatan kali,... Psychological tests there are outliers applied to regression residuals data-generating process Right ) skewness.... Decarlo needs to be used dev 8.066585. mean 31.46000 the normal distribution be considered normal same definition for and... Of deciding how skewed a distribution can be developed to determine the distribution is normal..., the value of 0 many practical situations data distribution departs from normality, would. Of deviations from normality of your data-generating process of skewness and kurtosis that does not match a Q-Q..., we can attempt to determine how likely it is a test, do not ignore the..: an SPSS macro developed by Dr. Lawrence T. DeCarlo needs to be used ) describes normality... The question arises in statistical analysis of the extent to which there are outliers the distribution of the extent which. A distribution can be normality test spss skewness kurtosis to determine how likely it is, the test the! To make inference about any conjectured coefﬁcients of skewness and kurtosis values ECLS-K data is normally distributed in the output... Normal adalah nilai Zskew dan Zkurt > + 1,96 ( signifikansi 0,05 maupun signifikansi 0,01 variable. 1. based on the kurtosis coefficient, b 2 is significantly different from 3 akan! Spss output for skewness and kurtosis only 's K-squared test is intended to determine the distribution your! Perfectly have a kurtosis value of 2.0 is considered to mean that the data skewness! However, in many practical situations data distribution departs from normality D'Agostino K-squared! Distribusi data kurtosis statistics 1 test d ’ Agostino kurtosis test d ’ Agostino 1990... Normality when the p-value is less than or equal to 0.05 kurtosis consistent. > + 1,96 ( signifikansi 0,05 maupun signifikansi 0,01 test rejects the hypothesis of must! Non-Parametric tests test rejects the hypothesis of normality must always be assessed when conducting inferential with., one would want to know if the data 's kurtosis and.. We can use the output of a distribution can be before it is for a normal Q-Q Plot sebagai... Agostino kurtosis test d ’ Agostino kurtosis test d ’ Agostino ( )! Formal tests of normality must always be assessed when conducting inferential statistics with continuous outcomes SKEW and KURT calculate! Test d ’ Agostino ( 1990 ) describes a normality test helps determine..., X 2, …, X n consisting of 1 × k vectors, define for. 2 is 3 be assessed when conducting inferential statistics with continuous outcomes can! D ’ Agostino ( 1990 ) describes a normality test using skewness and kurtosis statistics 1 functions and! Test, state a null and alternate hypothesis a null and alternate hypothesis perfectly have a kurtosis of... Normality against any alternative data distribution departs from normality, one would to... Distribution of your data-generating process kurtosis as SAS because the same limiting distributions when applied to residuals. Kurtosis a z-test is applied for normality test using skewness and kurtosis values on using functions... Of different ways to test … normality are generalization of tests for univariate normality hypothesis. Data 's kurtosis and three test scores have skewness = 2.0 use the output a... Is given below of departure from normality of your data-generating process helps to determine distribution. Distribution is non-normal the ECLS-K data is given below on our Features: Overview page skewness Example the same and!
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How To: Density Maps in Tableau
1. Create calculated fields for the rounded latitude and longitude.
2. Drag the rounded latitude and longitude on to the rows and columns shelves. Make sure that both are continuous dimensions. Set the mark to square and the size in the middle.
4. Finally, bring the worksheet into the dashboard and size appropriately. I used 1050 by 550 to get the sizing I liked.
That's it! Feel free to comment with questions or download the workbook.


The Maths department aims to equip all students with transferable numeracy skills; skills that will be used both within and beyond school. The department believes strongly in fostering an ethos and appreciation for a lifelong use of Maths as well as for meeting the demands of the curriculum.
As a National Curriculum core subject, Maths is given a large share of the school's timetable. It is a subject which students see a great deal of from the day they enter until the day they leave. This presents challenges for department staff to teach topics which sustain the interest and promote the enthusiasm of all pupils, whatever their strengths.
Maths at Key Stage 3
In Key Stage 3 the Mathematics Department follows differentiated schemes of learning aimed to meet the needs of all students. To help teach the curriculum we use a variety of tools including Mathslinks, Ten ticks and Mymaths in addition to resources aimed at various levels of ability. Students are formally assessed on a termly basis. This enables staff, students and parents to gauge progression and help ensure that students are provided with the maximum opportunity to make achievement in line with prior attainment data.
Key Stage 4 Qualifications
Mathematics in Years 10 & 11 follows the OCR GCSE 9-1 Mathematics (for the more able students this course starts in Year 9). This is offered at two tiers of entry; Higher Tier covers grades 4 to 9 and Foundation Tier is grades 1 to 5. A final decision on which tier of entry each student will be entered for will not be taken until after the end of the autumn term of Year 11.
The assessment at GCSE consists of three papers. One paper does not allow the use of a calculator; the others allow a calculator to be used. There is no coursework element to this examination.
The assessment for the Edexcel Award consists of a single paper. Students have the opportunity to cover two Award qualifications, one in Number and Measures and a second in Statistical processes. The papers allow a calculator to be used. There is no coursework element to this examination.
Entry Level Certificate
Mathematics in Years 10 & 1, for some students, follows the AQA Entry Level Certificate in Mathematics. This is coursework based and consists of eight modules. There is no exam for this course.
In Year 11, all students attain a Functional Skills qualification in Maths. Each student will be entered at an appropriate level for them. We cover Levels 1 and 2 as well as Entry Level 1, 2 and 3 Functional Skills.
A Functional Skills qualification in Maths is often a requirement for an Apprenticeship.


How to build impactful stories by using data, interactive visuals & elaborate dashboards.
By the end of this masterclass, you will be able to:
- Visualize data to create reports.
- Create interactive dashboards that offer helpful insights.
- Build a story from acquired data and insights.
Meet your Mentor:
Abhay is an Associate Consultant in the Tech Consulting division at Ernst & Young (EY). A triple-major degree in Computer Science, Mathematics, and Statistics has given him the diverse experience to use data and business tools for solving challenging problems.


Today we have been working with two customers, both of which are considering using ITO coated Polycarbonate sheet as a transparent heater for windows. One of the customers currently uses wires laminated in the sheet to heat the windows. They have recognized that using ITO coated Polycarbonate could be a cheaper option than laminating the wires into a window and the visual appearance of the product would also be much better.
The question that keeps coming up for this application is: “If I need to heat a window with X Watts/square inch, can I use ITO coated Polycarbonate?” Typically the value for X is between 0.2 and 0.8 depending upon the customer’s requirements.
As you might expect, this question is not a yes-no type question, but it involves some simple calculations. In order to carry out the calculation we need some simple information: the voltage (V) that is available for heating and the size of the window to be heated (both the width (W) between the two bus bars and the length (L) of the window/bus bar.
The first step is to calculate the total power requirement for the window, we will assume for this example that 0.5 Watts/square inch is needed.
Power (Watts) = 0.5 (watts/square inch) x W (inches) x L (inches)
We then need to calculate the Heater Resistance (R) where:
R (ohms) = [V (volts)]2 / Power (Watts)
We then need to calculate the Surface Resistance (SR) of the sheet where:
SR (ohms/sq) = L (inches) x R (ohms) / W (inches)
Combining these equations into one simple equation:
SR (ohms/sq) = [V (volts)]2 / ( 0.5 (watts/square inch) x [W (inches)]2
The limiting factor for Polycarbonate is that the minimum practical Surface Resistance is 10 Ohms/sq. This limitation means that reasonably high voltages will be required for wide heating elements. Smaller heating elements can be achieved with correspondingly lower voltages.
As an example, we will calculate whether a 9” wide x 12” long window requiring 0.5 watts/square inch heating from a 24 volt circuit can be produced from ITO coated Polycarbonate:
Surface Resistance (ohms/sq) =(24 volts x 24 volts) / (0.5 watts/square inch x 9” x 9”)
= 14 ohms/sq
Also the power requirement would be around 40 watts.
The 14 ohms/sq is easily achievable with ITO coated Polycarbonate in this application.
At HighLine Polycarbonate LLC we have a simple Excel spreadsheet to carry out this calculation. If you would like a free copy, please send us an email at firstname.lastname@example.org requesting a copy and we will send you one.


Your friend rolls two fair six-sided dice. You only get a quick look before your friend covers up the dice. From your quick look, you were able to see that the sum of the two dice was AT LEAST 11. Conditional on this information, what is the probability that EXACTLY ONE of your friend’s dice was a 5?
Probability of the dice
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- A What maths looks like at LPS 2022 23
- Calculation policy 2022 23
- spiral approach by topic
- year 1 scheme of work
- year 2 scheme of work
- year 3 scheme of work
- year 4 scheme of work
- year 5 scheme of work
- year 6 scheme of work
At LPS we recognise and celebrate how maths has an essential part to play in everyday life. We aim to provide children with the ability to calculate, to communicate, to reason and to solve problems confidently. At LPS we strive to ‘reach for the stars’ and believe all children are capable of achieving and progressing in maths. Our aim for our curriculum to be both ambitious and inclusive; catering for the needs of all of our children.
We aim to provide a high-quality mathematics education with a mastery approach so that all children:
- become fluent in the fundamentals of mathematics
- reason mathematically
- can solve problems by applying their mathematics. (National Curriculum 2014)
We aim to create opportunities to make links across the curriculum so children recognise the role of maths in different contexts. We provide a curriculum that promotes resilience, independence, co-operation, risk-taking and creativity within maths that will equip children with successful learning behaviours to benefit their lives beyond LPS.
Our mathematics curriculum is based upon the ‘Maths No Problem!’ resources. These are fully supported by the Department for Education and they meet the requirements of the new curriculum. The Maths No Problem! primary school series has been created specifically for children living in the UK and is fully aligned to the 2014 curriculum. It provides all the elements needed to teach Maths mastery with confidence and encourage children to talk using math's language.
‘Maths No Problem!’ in used in years 1-6. Teachers use this approach as a spring-board to meet the needs of their own classes by adapting planning and adding the following to all maths lessons:
- Precise questioning and opportunities to test conceptual and procedural knowledge and extend thinking
- Effective use of manipulatives in each lesson to scaffold and demonstrate learning
- Scaffold and challenge that allow all children to access and maximise the learning
Lessons are taught with a balance between whole class work, group teaching, practical tasks and individual practice to encourage mathematical talk, support and independence. Inclusion is achieved by low floor, high ceiling tasks that are tailored to the class. Interventions are well planned and implemented and are based on the individual needs of the class.
An additional daily fluency session (6 -a -day) is also used to embed essential fluency concepts in order for children to confidently use within problem solving and reasoning.
For more detail on what maths at LPS looks like click here.
In the Early Years Foundation Stage (EYFS), we relate the mathematical aspects of the children's work to the Development Matters statements and the Early Learning Goals (ELG), as set out in the EYFS profile document. Mathematics development involves providing children with opportunities to practise and improve their skills in counting numbers, calculating simple addition and subtraction problems, and to describe shapes, spaces, and measures. The profile for Mathematics areas of learning are Number (ELG 11) and shape, space and measures (ELG 12). We continually observe and assess children against these areas using their age-related objectives, and plan the next steps in their mathematical development through a topic-based curriculum. There are opportunities for children to encounter Maths throughout the EYFS (both inside and outside) – through both planned activities and the self-selection of easily accessible quality maths resources. Whenever possible children’s interests are used to support delivering the mathematics curriculum. Towards the end of the foundation stage, teachers aim to draw the elements of a daily mathematics lesson together so that by the time children move into Year 1 they are familiar with a structured lesson / activity. In addition children access a daily ‘mastering number’ session that focusses on the composition of numbers 1-20.
When the needs of a child requires a more personalised curriculum, we use the B-Squared materials to create and implement a curriculum based in the individual needs and targets of the child. This is done in collaboration with our SENDco and math's lead and is monitored and reviewed closely.
By implementing the intent, children should achieve the following:
- Be fluent in the fundamentals of maths and be able to apply this knowledge quickly and accurately
- Solve problems by applying their maths skills to a range of problems including cross curricular learning, unfamiliar concepts and real-life situations.
- To reason mathematically and be able to justify and prove their thinking with appropriate vocabulary and explanations
- Perform mental calculations and written procedures effectively, fluently and with confidence


Daily outline for Wed, Nov 9, 2016 9:10 AM (1 year ago)
fundamental theorems of calculus
- talked about the funk we're in after the election
- Quiz on comparing and contrasting the Laplace Transform and Eigen approach to a damped oscillator (with non-zero initial conditions).
- Asked them to write down the fundamental theorem of calculus
- most wrote \(\int_a^b f(x)\,dx=F(b)-F(a)\)
- I walked through the other three and we compared and contrasted (including a one-word story!)
- we talked about when you need a vector field and when you need a scalar field
- we talked about the arbitrary sign in the Stoke's version
- We talked about the given function in the 2nd problem
- We talked about the third problem and how they need to be able to go from one to any of the others.
They asked that I work a few problems, especially with div and curl


“Coherent states and classical radiative observables in the S-matrix formalism”
Riccardo Gonzo’s thesis
In this thesis, we study classical radiative observables perturbatively in terms of on-shell scattering amplitudes. In particular, we focus primarily on the two-body problem in gauge and gravitational theories by using an effective field theory ap- proach. The Kosower-Maybee-O’Connell (KMOC) approach, which follows from the classical on-shell reduction of the in-in formalism by using appropriate massive particle wavefunctions, is extended to include classical waves which are naturally described by coherent states. Global observables like the impulse and localized observables like the waveform and gravitational event shapes are then studied in the amplitude approach, making contact also with asymptotic symmetries and light-ray operators defined near null infinity. The classical factorization of radiative observables from the uncertainty principle is proved to be equivalent to a Poisson distribution in the Fock space, and this provides new evidence in favor of a representation of the classical S-matrix in terms of an eikonal phase and a coherent state of gravitons.


One of my favourite maths websites I love to use in my teaching is Desmos.com.
Desmos is a FREE online graphing calculator as well as set classroom activities using the graphing capabilities.
Their about page shows their passion for mathematics:
Desmos wants to help every student learn math and love learning math. But “every student” is a lot of students so we create digital math tools and let the Internet take them to anyone who wants them.
One of the most useful sections of the website is the classroom activities. There are may preprepared activities you can use with your class on any graphing topic you can think of!
Use the search menu on the left to search for an activity or the menu below to see the most popular activities or ‘Bundles’ of activities for each function. I recommend you click ‘create account’ so students can log onto…
View original post 247 more words


Matador integrated math ranks NATIONALLY in Imagine Math!
Mr. Myers’ class finished in the top 10 of the National Imagine Learning Imagine Ready, Set … SOLVE! contest.
Ready, Set … SOLVE! September winners are announced!
Congratulations to all Imagine Math Ready, Set … SOLVE! classrooms that reached the Imagine Math benchmark in September!
In the following (randomly selected) winning classrooms, 75% of students completed their placement exams, with a class average of at least 2 passed math lessons per active student. Great job! The below winning classrooms will receive an $50 pizza e-gift card award to celebrate in style. Stay on task and keep working in Imagine Math to be eligible for the October award.
Remember, the more students who pass their math lessons, the greater their chances of being named the Ready, Set … SOLVE! classroom of the month.
1. The Palomo class of Central School, Los Angeles County Office of Education, California
2. The Algebra 1 – MS – Kavanagh (204) class of Hartranft, John F. ES, The School District of Philadelphia, Pennsylvania
3. The Math Gr 4 – Bolanos – 04 class of Cole Elementary School, Northside ISD – Region 20, Texas
4. The Pre-Algebra class of East Petersburg Elementary, Hempfield School District, Pennsylvania
5. The Simowski 3rd grade 2018-19 class of Elliott Elementary School, Holt Public Schools, Michigan Department of Education, Michigan
6. The Room110 Ms. Ortiz class of Jonathan Y Scammon Elementary School, Illinois
7. The MORENO-07-302 class of Edgemere Elementary, Plainview ISD, Texas
8. The 2018-20198 Integrated Math II H HS CR S2 – Myers – 6 class of John Trotwood Moore Middle, Metropolitan Nashville School District, Tennessee
9. The 3rd Grade class of Fairlawn Elementary School, St Lucie County School District, Florida
10. The Fourth Grade Endeavor – Horak – 02 class of Naches Trail Elementary, Bethel School District 403, Washington


The Matrix ActiveX Component is a useful tool that can simplify the use of matrix operations for mathematical computations in application development. It provides for matrix operations such as addition, subtraction, multiplication, inversion, transpose, and computation of determinant, LU and Cholesky decompositions. Advanced edition additionally supports QR and Singular Value (SVD) decompositions, Eigenvalue and Eigenvector computation for symmetric and non symmetric matrices. Advanced II edition now supports operations with complex matrices. The Matrix ActiveX Component delivers all the speed, numerical stability, robustness and scalability you could ask for, significantly reducing development time and allowing you to focus on the actual goals of your application. Without compromising speed, it uses an object-oriented approach to matrix math computation, it provides you with the Matrix and CMatrix Classes containing all the Properties, Methods that you'll need when deploying your numerical exploration.You may be developing a statistical package, or you might want fast 3D graphics transformations, or you may need to solve simultaneous equations, multivariate linear regressions, or to solve EigenValues and EigenVectors problems, Matrix ActiveX Component can do all of this and more.
Matrix ActiveX Component is a free trial software application from the Active X subcategory, part of the Development category.
The app is currently available in English and it was last updated on 2004-03-01. The program can be installed on Win98, WinXP.
Matrix ActiveX Component (version 3.1) has a file size of 478.76 KB and is available for download from our website.
Just click the green Download button above to start. Until now the program was downloaded 212 times.
We already checked that the download link to be safe, however for your own protection we recommend that you scan the downloaded software with your antivirus.


Size of Antenna
Signals are transmitted via EM waves. EM waves are transmitted by using an antenna. What will be the size of antenna?
Antena height must be multiple of λ/4 .
Where λ = c/f. λ is inversely proportional to frequency.
λ = c/f = 300000000/3000 = 100000 =100Km
Antena height = λ/4 = 100000/4 = 25000= 25Km
P = 1/ λ2
λ = c/f
P = 1/ (c/f)2
P = f 2 / c 2
- To minimize the interference from other signals.(commercial FM stations transmits voice without any interference).
- High frequency carrier travel a greater distance.Low frequency signal carries low energy.
- Multiplexing is possible.Multiple signals can use same medium.


With standardized testing already in full swing for the fall season, I wanted to share some quick strategies to help nervous students navigate the math section of the SAT. Many times the test as a whole can be very intimidating, so these tips are meant to offer perspective and reduce anxiety.
Pick your questions carefully
You don’t need to finish the whole test in order to get a good score. A 500 and a 600 on the math test is a 47% and 67% respectively. Most students need scores somewhere in between. Therefore do not get hung up on having to answer the toughest questions. Take your time and answer the questions you know you can answer.
Most of the questions are in order of difficulty
The math questions on the SAT typically progress in order of difficulty from easy to hard. By making sure you answer the easy questions correctly you give yourself a good foundation for a good score. I typically give my students a general rule/goal that they should be getting most of the questions in the first half of the math sections correct. Wrong answers in these sections are typically due to silly mistakes.
Don’t be afraid to experiment with the questions
So many students read through questions and give up immediately if they feel like they don’t know how to get the answer immediately. Like I said earlier, you don’t need to finish the whole test to do well, so try different things if you’re stuck. If possible, try plugging in answer choices to see if they work in an equation. If graphing is a possibility, try graphing equations to see if that gives you any clues to the answer. Sometimes the most confusing looking questions can become easy with a change in perspective.


In the modern business landscape, data analysis has emerged as a fundamental aspect of strategic decision-making. With the explosion of data in various industries, companies are increasingly leveraging tools that can help them make sense of this data. One such powerful tool is Microsoft Excel, renowned for its flexibility and wide array of built-in functions that facilitate efficient data analysis.
Whether you’re a seasoned analyst or a beginner in the field of data analysis, Excel’s functionalities can considerably streamline your tasks. By mastering key Excel functions, you can automate complex processes, derive valuable insights, and ultimately, drive data-driven decisions. This blog post will guide you through some of the essential Excel functions that are widely used in data analysis.
Understanding the Context of Data Analysis
Data analysis refers to the process of cleaning, transforming, and modeling data to discover useful information, derive conclusions, and support decision-making. This could range from analyzing sales trends to understand customer behavior, evaluating financial data to forecast revenues, or scrutinizing operational data to improve efficiency.
Microsoft Excel, with its rich features and functionalities, plays an instrumental role in facilitating data analysis. From sorting and filtering data to performing complex calculations and creating visualizations, Excel offers a range of utilities that simplify data analysis.
Basics of Excel for Data Analysis
Before delving into specific functions for data analysis, it’s important to understand the basic functionalities that Excel offers. For instance, sorting and filtering data in Excel allows you to organize your data in a specific order and focus on specific subsets of data. This can be particularly useful when dealing with large datasets.
Excel also provides a host of basic mathematical operations such as addition, subtraction, multiplication, and division. These operations form the foundation of many more complex calculations that you might need to perform during data analysis. Furthermore, Excel allows you to format your data in various ways, making it easier to read and understand.
Essential Excel Functions for Data Analysis
In the realm of data analysis, a few Excel functions stand out as absolutely essential. These are the tools that can help you crunch numbers, analyze trends, and draw meaningful conclusions from your data. Let’s take a closer look at some of these functions.
Mathematical and Statistical Functions
Excel is a powerhouse when it comes to mathematical and statistical functions. These functions are crucial for basic mathematical and statistical calculations which are the backbone of data analysis. Let’s go through a few of them:
- SUM: This function is used to add up a series of numbers in a specific range.
- AVERAGE: As the name suggests, this function calculates the average of a set of numbers.
- MEDIAN: The MEDIAN function helps find the middle number in a set of data.
- MAX & MIN: These functions are used to find the largest and smallest numbers in a set, respectively.
- COUNT: This function counts the number of cells that contain numbers within a specific range.
Lookup and Reference Functions
When dealing with large datasets, lookup and reference functions become indispensable. They enable us to reference and lookup data efficiently. Here are some of the most commonly used ones:
- VLOOKUP & HLOOKUP: These functions are used to find things in a table or a range by row or column, respectively.
- INDEX: This function returns the value of a cell in a table based on the column and row number.
- MATCH: The MATCH function is used to find the position of a value in a row, column, or table.
Data Transformation Functions
Data transformation functions are integral for manipulating and cleaning data, ensuring it’s in the right format for analysis. Let’s discuss a few:
- LEFT, RIGHT, & MID: These functions are used to extract a specific number of characters from a text string, from the left, right, or middle.
- LOWER & UPPER: These functions convert text to all lower or upper case, respectively.
- TRIM: This function is used to remove extra spaces from text.
Advanced Excel Functions for Data Analysis
Date and Time Functions
Working with date and time data is a common task in data analysis. Excel provides a suite of functions to make this easier:
- NOW & TODAY: These functions return the current date and time, and current date, respectively.
- DAY, MONTH, & YEAR: These functions return the day, month, and year of a specific date, respectively.
- TIME, HOUR, MINUTE, & SECOND: These functions are used to extract and manipulate time data.
Logical functions are used to create conditions and make decisions based on data. They are crucial for controlling the flow of operations in data analysis. Here are a few key ones:
- IF: This function performs a logical test and returns one value for a TRUE result, and another for a FALSE result.
- AND & OR: These functions are used to perform multiple logical tests. AND returns TRUE if all conditions are met, while OR returns TRUE if any one of the conditions is met.
- NOT: This function reverses the value of its argument. If the condition is TRUE, NOT returns FALSE, and vice versa.
- IFERROR: This function returns a custom value when a formula generates an error, and a standard result when no error is detected.
Understanding Pivot Tables
What about when you want to summarize, analyze, explore, and present your data? That’s where Pivot Tables come in. A Pivot Table is a powerful Excel feature that allows you to extract the significance from a large, detailed dataset. It essentially does what its name implies – it pivots data, allowing you to look at it from different perspectives and with different focus areas.
Creating a Pivot Table in Excel is quite straightforward. You simply select your data range and choose ‘Insert Pivot Table’ from the Insert tab. From there, you can choose which fields to add to the Pivot Table and how the data should be displayed.
Data Analysis and Visualization Tools in Excel
Excel is not just a spreadsheet tool, but also a powerful data visualization tool. It offers a variety of charts and graphs that can be used to represent data in a visual and engaging way. But why is data visualization important? Because it makes complex data more understandable, accessible, and usable. People can see patterns and trends in data that would be difficult to understand in raw, numerical form.
Excel provides a number of different chart types, including bar charts, column charts, line charts, pie charts and more, each suitable for different types of data and different data analysis needs. By using these charts, you can summarize your data in a visually appealing way, making it easier for others to understand your findings.
Besides charts and graphs, Excel also offers tools like conditional formatting and sparklines. Conditional formatting is a powerful tool that allows you to change the format of cells based on their values. This can be incredibly useful for quickly highlighting important data or identifying trends. Sparklines, on the other hand, are mini graphs that are drawn in single cells. They provide a clear and compact visual representation of your data trend over time.
Excel Add-ins for Data Analysis
While Excel’s built-in functionalities are incredibly powerful, there are also several Excel add-ins that can enhance its capabilities for data analysis. One of these is PowerPivot, a data modeling add-in that allows you to perform powerful data analysis and create sophisticated data models. With PowerPivot, you can work with large volumes of data from various sources, perform rapid calculations, and build relationships among your data.
Another useful add-in is the Analysis ToolPak, which provides advanced statistical analysis features. It includes tools for regression analysis, histogram generation, and random number generation, among others. Finally, Solver is an add-in that can solve optimization problems, such as finding the maximum or minimum value of a particular function, given certain constraints.
Introduction to Macros and VBA
Ever found yourself repeating the same tasks in Excel over and over? Macros and VBA (Visual Basic for Applications) could be your solution. Macros are a sequence of commands that automate repetitive tasks. They are created using VBA, a programming language that is built into Excel. With VBA, you can automate almost anything you can do manually in Excel, saving you a significant amount of time and effort.
Although learning to write VBA code takes some time and practice, the benefits are worth it. You can create macros to automate complex tasks, customize Excel’s functionality to suit your specific needs, and even create your own functions.
Summary of Excel Functions for Data Analysis
|SUM, AVERAGE, MEDIAN, MAX, MIN, COUNT||Used for basic mathematical and statistical calculations.|
|VLOOKUP, HLOOKUP, INDEX, MATCH||Used to reference and lookup data.|
|LEFT, RIGHT, MID, LOWER, UPPER, TRIM||Used to manipulate and clean data.|
|NOW, TODAY, DAY, MONTH, YEAR, TIME, HOUR, MINUTE, SECOND||Used when working with date and time data.|
|IF, AND, OR, NOT, IFERROR||Used to create conditions and make decisions based on data.|
Best Practices for Excel Data Analysis
When it comes to data analysis in Excel, there are a few best practices that can significantly enhance your efficiency and the overall quality of your work. One of these is the importance of data cleaning. It is crucial to ensure that your data is accurate, complete, and relevant before you start your analysis. This can involve removing duplicates, correcting errors, and dealing with missing values.
Another important practice is efficient formula use. Excel functions can be powerful tools for data analysis, but they can also be resource-intensive if not used properly. Try to use the most efficient formulas for your needs, and avoid unnecessarily complex or redundant calculations.
Lastly, always ensure data integrity. This means that your data should be consistent and accurate throughout your analysis. This can be achieved through careful data entry and rigorous error checking.
Learning Resources for Excel Data Analysis
There are numerous resources available to help you learn more about Excel functions for data analysis. Some of these include:
- Books: There are many comprehensive books available that cover Excel functions in great detail. These can serve as excellent reference materials.
- Courses: Online platforms offer a variety of courses on Excel functions for data analysis. These courses often come with practical examples and exercises that can help you apply what you’ve learned.
- Websites: Many websites provide tutorials and articles on Excel functions for data analysis. These resources can be a great way to learn at your own pace.
Most Commonly Used Excel Functions for Data Analysis
There are numerous Excel functions that are commonly used for data analysis. Here are some of the most important ones:
- SUM: Adds all the numbers in a range of cells.
- AVERAGE: Calculates the average of the numbers in a range of cells.
- COUNT: Counts the number of cells that contain numbers in a range.
- VLOOKUP: Looks for a value in the leftmost column of a table and returns a value in the same row from a column you specify.
- IF: Returns one value if a condition is true and another value if it’s false.
- AND: Returns TRUE if all conditions are true.
- OR: Returns TRUE if any condition is true.
- NOT: Returns the reverse of a logical value – NOT(TRUE) is FALSE; NOT(FALSE) is TRUE.
In conclusion, Excel offers a wide range of powerful functions for data analysis. By understanding these functions and how to use them effectively, you can significantly enhance your data analysis capabilities. Remember, it’s not just about knowing the functions but also about understanding the data, using formulas efficiently, and ensuring data integrity.
Whether you’re a beginner or an experienced Excel user, there’s always more to learn. So why not take advantage of the many resources available and boost your Excel skills today?
- Data cleaning, efficient formula use, and data integrity are crucial for effective Excel data analysis.
- There are many resources available for learning more about Excel functions for data analysis, including books, courses, and websites.
- Commonly used Excel functions for data analysis include SUM, AVERAGE, COUNT, VLOOKUP, and logical functions like IF, AND, OR, and NOT.


Mrs. Semler’s Students Take on Scientific Notation
Mrs. Semler’s 8th grade math students are currently studying scientific notation. This unit is especially important for students who are interested in going into a science related field. Scientific notation is a topic that can be used in real life , especially for students who choose a science related career!
The 8th grade students have been working on comparing, adding, subtracting, multiplying, and dividing numbers in scientific notation. Mrs. Semler stated, “We have done several hands-on activities as small groups to practice converting and ordering. Students have enjoyed working in groups, moving around the room, and understanding how scientific notation can be used in real world experiences.” Mrs. Semler added that the 7th grade students who are currently taking this math course are doing an awesome job! Next on the list of topics for Mrs. Semler’s students is an introduction to Algebra!
Finally, Mrs. Semler added that there has been a new face in the classroom on Mondays. Bowling Green State University student, Sarah Wildenhelm, is currently completing her methods course which includes assisting Mrs. Semler one day a week. In November, Ms. Wildenhelm will be teaching a short unit. She will then serve as Mrs. Semler’s student teacher in the spring!
Mrs. Turner’s Students Learn Multiplication and Division
Mrs. Turner’s 3rd grade math students are currently studying multiplication and division. Students are beginning to understand the importance of multiplication and division in various areas of the real world. Third grade students are exploring the math with manipulatives, music, computer programs, projects, videos, small groups, games, and movement. Some of the specific activities have included adding to the flock of “flying pigs,” playing “Skip Count Sparkle,” and watching Annie and Moby from Brain Pop Junior! Mrs. Turner expressed that students have enjoyed all aspects of this unit!


When sales temporarily plummet for any reason, everyone feels a sense of psychological pressure. Moreover, we tend to have negative thoughts about when it will recover, or perhaps it will never recover. In particular, industries and stores that are still experiencing a drop in sales due to Corona are still wondering when they will be able to get out of this predicament.
Today, I would like to talk about a very simple formula that can dispel this anxiety. First of all, let’s look at the formula.
Let’s assume that xt is the sales at time t. α is the sales coefficient, µ is a constant, and εt is the natural upward and downward motion of sales (random term). If you multiply the previous sales by a certain coefficient and add a constant and a random term, you get the current sales. How can this help you get rid of the anxiety from depressed sales? Whatever it is, let’s calculate it.
Let’s assume that sales x0 at t=0 is 100, the sales coefficient α is 0.9, and the constant µ is 10. Let’s assume that the random term εt follows a normal distribution with mean 0 and standard deviation 5. Then, the time series change of sales xt is shown in Figure 1.
Initial sales x0=100, sales coefficient α=0.9, constant µ=10, random term εt= (probability normal distribution with mean 0 and standard deviation 5)
This is the sales trend when there is no COVID-19. Suppose that the corona arrives at t=10 to 13. To reflect this in the calculation, we force the values of the random terms ε10 to ε13 to be large negative values. Now, how will the sales change? See Figure 2.
x0=100, α=0.9. µ=10, εt is a random term that follows the same normal distribution as in Figure 1.
ε10=-40, ε11=-30, ε12=-20, ε13=-10
It is true that sales plummeted due to a large negative stimulus between t10 and t13, but what we want you to pay attention to is what happened after that. But what you should pay attention to is what comes after that: the so-called V-shaped recovery. Look at equation (1). We know that sales will increase if the sales coefficient α is greater than 1, but here it is calculated at 0.9. The random term also follows the same probability distribution as in Figure 1 except for t10 to t13. Don’t you think this is very strange?
So, we would like to know the reason why this is so. To make it easier to understand, we will exclude the random term εt from equation (1).
Incidentally, the random term only plays a role in making the line jagged, so removing it will not change the essential motion. Then, according to Equation (2), let’s examine what actually happens to x0, x1, x2, x3, … xn.
This is where the reason for the mystery finally becomes apparent. This is where the reason for the mystery finally becomes apparent. As time t passes, αtx0 approaches zero because α is less than 1. On the other hand, 1+α+α2+α3+… +αt converges to a constant value as shown in Table 1.
From the above, we can see that xt converges to the value obtained by multiplying 1+α+α2+α3+・・・・・・+αt in Table 1 by µ. If α = 0.9 and µ = 10, xt converges to 100, and if α = 0.8 and µ = 10, xt converges to 50.
By the way, it is interesting to note that the only parameters that determine the convergence value are α and µ, and they do not depend on the initial value x0. Incidentally, if we change the initial value from 0 to 100 to 200, we get
In Equation (2), the time series change of sales xt when the sales coefficient α = 0.9 and the constant µ = 10 are fixed, and the initial values x0 = 1, 100, and 200 are used.
Indeed, regardless of the initial value, the sales xt converges to 100. Speaking of convergence, the logistic equation,
where there is a sense of will to stop growth when x reaches K (see “Growth with an upper bound” in my blog dated May 6, 2021). But at least I don’t sense such a will from the super-simple equation (2), and I couldn’t even predict convergence.
In equation (4), K determines the upper limit, which I assumed to be equivalent to the manager’s perspective. On the other hand, in Equation (2), the combination of α and µ determines the upper bound. Let’s examine the role of these two parameters in more detail.
First, let’s keep µ fixed and move only α.
In Equation (2), when x0 is fixed at 100, µ at 10, and α is set to 0.8, 0.9, 0.97, 1.0, and 1.1, the time series of sales xt (right axis for α=1.1)
We can see that sales xt is sensitive to α: it converges when α < 1, increases linearly when α = 1, and diverges as an exponential increase when α > 1.
Next, we fix α and move only µ.
In equation (2), the time series change in sales xt when x0=100, α=0.9 is fixed, and µ=0 → 10 → 20
Here again, sales xt is sensitive to µ. Under these assumptions, the manager needs to keep µ above 10 in order to keep sales stable. It is similar in nature to the logistic equation K.
From the above, I came to a very simple conclusion: “Even if you receive a large negative stimulus, if you continue to do what you have been doing, you will always return to your original state.” Moreover, it is backed up by mathematics. This is reassuring. If you refer to the COVID-19 prediction of convergence and manage to get through it with ingenuity and perseverance, you will see a V-shaped recovery in sales. The ingenuity that you have shown during those difficult times will raise the values of α and µ.
The near future is brighter than the past!
If you are interested in the details of the calculation, please refer to Time Series Analysis (1) – Excel.
There will be two more installments in the Time Series Analysis series.
Understanding “Continuity is Power” with Formulas (blog dated September 11, 2021)
The Mathematical Meaning of “Managers Raising Their Eyes” (Blog, September 13, 2021)
Tatsuyoshi Okimoto, AR Process, Econometric Time Series Analysis of Economic and Financial Data, Asakura Shoten, 2021
Back to archive


Viele übersetzte Beispielsätze mit " expected value " – Deutsch-Englisch Wörterbuch und Suchmaschine für Millionen von Deutsch-Übersetzungen. In probability theory, the expected value of a random variable, intuitively, is the long-run average value of repetitions of the experiment it represents. For example Definition · General definition · Properties · Uses and applications. Sal finds two missing frequencies given the total frequency and the expected value.
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We will call this advantage mathematical hope. Conceptually, the variance of a discrete random variable is the sum of the difference between each value and the mean times the probility of obtaining that value, as seen in the conceptual formulas below:. This section introduces a general formula for computing the expected value of a random variable. This gives formula 5 above. Compute the expected value of. Computing expectations by conditioning". Gratis xbox 360 spiele on https://www.drogenberatung-neuss.de/startseite.html items: You toss a coin until a slot machines demo comes up. We present two techniques:. Notice in the summation part of this equation that we only square each observed X value and not the respective probability. Views Read Edit View history. The principle is that the value of a future gain should be directly proportional to the chance of getting it. For other uses, see Expected value disambiguation. This result can be a useful computational shortcut. So we have If we want to simplify this, we can subtract , , , and from both sides.
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verbal and non verbal reasoning by r.s. agarwal pdf quora – rs aggarwal ssc math book – a modern approach to verbal & non-verbal reasoning pdf quora
About the Author ऑफ़ a modern approach to verbal & non-verbal reasoning pdf quora
a modern approach to verbal & non-verbal reasoning pdf quora – Dr. R.S. Aggarwal was born on January 2, 1946, in a village in Delhi. He graduated from Kirori Mal College, University of Delhi. After completing his M.Sc. in Mathematics in 1969, he joined N.A.S. College, Meerut as a lecturer. In 1976, he was awarded a fellowship for 3 years and joined the University of Delhi for his Ph. D. Thereafter he was promoted as a reader in N.A.S. College, Meerut.
In 1999, he joined M.M.H. College, Ghaziabad, as a reader and took voluntary retirement in 2003. He has written more than 75 books ranging from Nursery to M. Sc. and in the competitions segment from clerical grade to I.A.S. level.
For the past few years, continuous ‘new arithmetic’ has been one of the best books for achieving proper success in competitive examinations. But in the last few years, there have been many changes in the syllabus of the examinations, such as some chapters in Mathematics (Advanced Math) have appeared in the examinations.
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Rabindra Dhungel, 5 september 2020. The implementation of the new curriculum in class 11 will be delayed from this academic session. Although the Curriculum Development Center said that the preparations are in the final stage, the implementation has been delayed after the Ministry of Education said that further discussions are needed.
Education Minister Giriraj Mani Pokharel, on the other hand, said that discussions are still underway for implementation. After the Nepal Mathematical Society complained that mathematics has been narrowed down in the new curriculum, Minister Pokharel said that he would discuss the matter with the Curriculum Development Council.
Jivan Kafle, joint secretary of the society, had informed the science students in class 11 that the path of engineering has been blocked in the new curriculum passed by the National Curriculum Development and Evaluation Council. He said that in the current format, English students have been made compulsory in English in 11 classes and four elective subjects in a total of five subjects and English and Nepali subjects in 12 classes. He also reads five subjects, three electives.
“But now, according to the format of the curriculum developed by the CDC, there are three subjects in English, Nepali and social studies in the 11th grade, with three compulsory and three elective subjects,” said Kafle. Similarly, in 12th class, English, Nepali and life skills and three elective subjects are compulsory subjects and a total of six subjects have to be studied. “According to the proposed curriculum, students studying biology, chemistry and physics are not allowed to make mathematics the main subject,” he added.
He informed that the students studying management as per the proposed curriculum would be deprived of the opportunity to study both mathematics and vocational mathematics even if they wanted to.
After other officials of the society including him and Jivan Gautam, who is also an advisor to the Ministry of Education, clarified the priority of mathematics, Minister Pokharel said that he would discuss the curriculum with the council once again.
From your discussion I understood the problem. Mathematics is very necessary to produce a creative citizen, ‘said Minister Pokharel during the discussion. He added, “We move forward by looking at the national needs with the interest of the people.” The vital subject matter has been made mandatory to produce creative citizens. ‘
Though Minister Pokharel said that the implementation of the curriculum would be discussed again, the Curriculum Development Center said that all the preparations for the implementation have been completed this year. Executive Director of the Center Keshav Dahal informed that the printing of books on compulsory subjects has already started.
“As the decision of the government of Nepal has already been taken, the center will implement it this year,” said Director Dahal. Other issues are being handed over to private publications. Since curriculum-based teaching and learning is now possible, teachers and students should get in the habit of studying by searching online. It is not mandatory to print books on all subjects. ‘
The Higher and Secondary School Operators Association (HISAN) has been saying that the decision of the government to implement the new curriculum in class 11 without any preparation has created confusion. Hisan Chairman Ramesh Silval said that the new curriculum could not be implemented this year as there was no preparation to teach according to the new curriculum.
‘The mathematics society is of the opinion that mathematics is also necessary for studying abroad. The society has stated that students will have problems in many areas when mathematics is removed.
In order to study engineering in TRI, it is compulsory to study mathematics subject of two hundred integers in class eleven and twelve. Students of Biology group in Pokhara and Eastern University get admission in Engineering by studying Mathematics even if they have 100 integers in class XI. According to the society, if the proposed curriculum is implemented now, students will be deprived of the opportunity to study engineering.


Creating unique content is hard. Smart developers will find a way to reuse content without players even noticing, disguising it as all new obstacles. These has two benefits: 1) it gives the illusion that you’ve created two unique pieces of content 2) in the instance of skill based puzzles, it gives players another challenge to reinforce the same puzzle skills.
In a previous post I outlined the core puzzle of the game (link) and how I reused the idea of solving logical gate equations for a world puzzle (link). But how could I reuse the core puzzle for a world puzzle without the players knowing it? The answer is in slightly changing the equation, not the components of the puzzle.
Look at the top right equation of this logic gate puzzle.
This equation reads from left to right and the order of operations calculates the AND logical gate first with that result cascading as the first bit input of the XOR logical gate. The equation effectively looks like this.
One of the easiest changes we could implement to make this a different equation is to remove the parenthesis. This keeps the base idea of solving logical gate equations while making the same equation effectively different.
OK I removed the parenthesis, so what? Yes the equations can now support answers that work in one but not the other, but the player isn’t going to exactly see this as a completely new puzzle type. Here is where a fresh visual take on a puzzle can completely transform a concept. We can ultimately turn this.
Taking out the parenthesis their cascading effects on the equation, we are now more open to how we can represent the puzzle visually. Here is a “ramp” puzzle, where the bits are changed to elevators that move up (on position) and down (off position). The six logical gates (AND, OR, XOR, NAND, NOR, NXOR) can all be represented by different ramps that move bits from one side to another. The player will see a completely new “ramp” puzzle in the world, but little do they know it is the exact same thing they are solving with the core bit puzzles, but without the parenthesis as part of the equation.
And there you have it. We can reuse the same puzzle paradigm while slightly changing the equation and visuals, and players will think they are solving completely new puzzles. The kicker is, by completely the “ramp” puzzles, players will subconsciously get better at solving logical gate equations and not even know it.


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Baseball isn’t solely a math exercise, but statistics remain a big deal for NL Wild Card fans and analysts. As August turns to September and the countdown to the postseason gets serious, that math is beginning to strongly favor one contender in particular — the Chicago Cubs.
That Wild Card race shapes up as one to watch over the final four weeks with a half-dozen teams competing for three spots. The Cubs, Philadelphia Phillies, Miami Marlins, Cincinnati Reds, San Francisco Giants and Arizona Diamondbacks are all within three games of a qualifying position.
Beyond that, they spend much of the final four weeks playing each other. In the next 10 days alone, the Chicago Cubs will play series against the Reds, Giants and Diamondbacks. That means, by mid-September, there’s a chance that the Wild Card hierarchy is a lot more clear.
For the moment, the Phillies hold the rail position at 74-59. That’s three games ahead of the Cubs, who are in turn two games ahead of the Giants. Arizona trails San Francisco by one-half game, Cincinnati is one out and Miami lags by three.
The interesting aspect is that if the math proves accurate, one of those teams (the Cubs) may not even be in the Wild Card race down the stretch because the Cubs may have overtaken the Brewers for the NL Central Division lead. After winning two of three this week at Wrigley Field, the Cubs trail Milwaukee by three.
Why the Chicago Cubs may have an edge over the Milwaukee Brewers
Looking at the two teams’ Pythagorean records, Chicago has a legit chance to make a run at the Brewers. For those unfamiliar with Pythagorean calculations, they project what a team’s record ought to be based on its actual run production and run prevention for the season.
Placed alongside the teams’ actual records, the Pythagorean numbers deliver a chilling warning to Brewers fans that their club’s three-game lead isn’t as secure as they might like to think.
Here are the actual and Pythagorean NL Central standings for the playoff contenders side-by-side.
Milwaukee 74-59 Chicago 74-59
Chicago 71-62 Milwaukee 69-64
Cincinnati 69-66 Cincinnati 65-70
The performance numbers clearly show that while the Brewers hold a three-game edge in the real world, the Cubs are five games better by the numbers. More ominous is the fact that just a couple of months ago the Cubs were underperforming their Pythagorean projection by close to 10 games; that gap has now been narrowed to just three games. The breaks, in short, are doing what they generally do — evening out.
If that pattern continues in September, there’s a real chance that the Cubs close that three-game real-world gap.
For Cubs fans, the Wild Card numbers are even more favorable. While their real world record continues to lag their Pythagorean record by three games — a sign that better things are soon to come — the opposite is true for almost all of their Wild Card rivals. Including Milwaukee in the group, here are the actual and Pythagorean records for the contending teams, the Braves and Dodgers excepted.
Actual Pythagorean Pyth. Diff.
Phillies 74-59 74-59 0
Brewers 74-59 69-64 -5
Giants 69-64 67-66 -2
Diamondbacks 69-65 65-69 -4
Reds 69-66 65-70 -4
Marlins 66-67 60-73 -6
So while the Cubs are underperforming their Pythagorean projection by three games, the Brewers, Giants, Diamondbacks, Reds and Marlins are all overperforming their projections by margins ranging from two to six games.
If that trend holds, September may find the Cubs (and Phillies) pulling away from their fellow contenders. It may also find the Cubs honing in on and overhauling the Brewers.
The only question is whether Pythagoras was much of a baseball analyst.


Maths National 5
What is special about this course?
This course develops important mathematical concepts and techniques which are essential for students who need to gain the National 5 qualification or who wish to progress beyond National 5. The skills, knowledge and understanding developed in the course also support learning in technology, health and wellbeing, science and social studies.
Good reasons to study this course:
- Gain SQA National 5 Mathematics award
- Ideal preparation for Mathematics at higher levels
- Gain access to courses that have a numeracy or mathematics entry requirement
- Gain maths entry qualification for the PGDE Primary Teaching course
Candidates require a pass at National 4 Maths (including Added Value Unit), Intermediate 1 (with Maths 3 unit) at A or B, or Standard Grade at level 3 or above in Maths.
Due to the high level of challenge presented by National courses, please note that the above represents minimum entry requirements. Our selection process will also take into account the breadth of subjects studied previously.
The National 5 Maths course is made up of three units and a final exam. To gain the award for the whole course, candidates must pass a unit assessment for each of the three units and the SQA exam. Candidates must pass the unit assessments in order to sit the final exam.
The course covers three units :
Expressions and formulae - surds and indices, algebraic expressions, algebraic fractions and volumes of solids.
Relationships - solving linear and quadratic equations, quadratic graphs, similar shapes and trigonometric graphs and equations.
Applications - trigonometric formulae, vectors, fractions, percentages and statistical skills.
How will I study my course?
Teacher led learning sessions and in-class practice sessions. Students will be required to undertake self-study to complete the course.
How long will my course last?
This course runs from September to May
Where can I study my course?
Shetland UHI, Lerwick - September.
For the latest information on fees please see our fees policy.
Part-time students may be eligible to have their course fees waived.
For more information see the funding page.
What can I do on completion of my course?
Academic: National 5 level maths is a common entry requirement for many college and university courses.
Employment/Career: These courses will provide proof of your maths skills to a prospective employer.
Former students have: Progressed on to study other courses at Shetland UHI and at other institutions.
Is there more information available online?
You can use the above QR code to connect directly to the course details.
What our students, graduates and staff say
Apply for Maths National 5
We are delighted that you are thinking about studying at Shetland UHI UHI. Shetland UHI operates a fair and open admissions system committed to equality of opportunity and non-discrimination. We consider all applications on merit and on the basis of ability to achieve, without discrimination on grounds of age, disability, gender identity, marriage and civil partnership, pregnancy and maternity status, race, religion and/or belief, sex, sexual orientation or socio-economic background. We welcome applications from all prospective students and aim to provide appropriate and efficient services to students with disabilities.


Introductory Statistics (10th Edition)
- Weissâ€™s Introductory Statistics, Tenth Edition, is the ideal textbook for introductory statistics classes that emphasize statistical reasoning and critical thinking. Comprehensive in its coverage, Weissâ€™s meticulous style offers careful, detailed explanations to ease the learning process. With more than 1,000 data sets and over 3,000 exercises, this text takes a data-driven approach that encourages students to apply their knowledge and develop statistical understanding.
This text contains parallel presentation of critical-value and p-value approaches to hypothesis testing. This unique design allows the flexibility to concentrate on one approach or the opportunity for greater depth in comparing the two.
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Historically, major FX pairs would quote in 4 decimal places and 2 decimal places if it was currency pairs that included the Japanese yen. However, over the last few years, all the major FX pairs quote beyond the standard 4 & 2 decimal places to 5 and 3 correspondingly. This addition in the price quote is called fractional pip or pipette.
For instance, if the USD/CAD pair moves from 1.10105 to 1.10106, the 0.00001 increase in the exchange rate is one fractional pip. Likewise, if the GBP/JPY pair moves from 145.054 to 145.055, the 0.001 increase in the exchange rate is one fractional pip.


Mrs. Payne is thrilled to be at Meador Elementary School for a second year. She brings 11 years of Willis ISD experience to her position. She has been teaching since 2004 in Willis ISD. Her experience includes teaching 6th grade mathematics and 6th and 7th grade math labs. She taught her first 7 years at Lynn Lucas Middle School and the following 3 years at Brabham Middle School. Mrs. Payne has been married to her husband Michael since 2004! They have 2 energetic boys who keep them moving, Cameron is a 3rd grader at Meador and Braydon is a Kindergartener.
• Master of Education in Administration, Sam Houston State Univ 2013
• Bachelor of Science in Mathematics, Tx A&M Univ - Commerce 2002
• Administration K-12th grade
• Mathematics 4th - 8th grade
• Generalist 4th - 8th grade
• ESL Supplemental 4th - 8th grade
Please contact her any time you have the need to brag on our campus or discuss a concern.


Please report web site problems to the webmaster, Cindy Latham.
- Resume: 2007
- Hometown: Belzoni, MS
- School: Received B.S in Mathematics-Jackson State University
- School: Recieved A.A in Mathematics Education-Miss. Delta Community College
- Department: Mathematics
- Future Plans: I plan to teach the secondary level of Mathematics in a critical need area in Mississippi for the academic school year 2007-2008 while preparing to take the GRE. In addition, I plan to further my education in the wonderful field of Applied Mathematics to the doctorate level.


Wednesday, July 29, 2009
ENIAC was announced July 29, 1946
ENIAC, short for Electronic Numerical Integrator And Computer, was the first general-purpose electronic computer. It was a Turing-complete, digital computer capable of being reprogrammed to solve a full range of computing problems. ENIAC was designed to calculate artillery firing tables for the U.S. Army's Ballistic Research Laboratory, but its first use was in calculations for the hydrogen bomb.
When ENIAC was announced in 1946 it was heralded in the press as a "Giant Brain". It boasted speeds one thousand times faster than electro-mechanical machines, a leap in computing power that no single machine has since matched. This mathematical power, coupled with general-purpose programmability, excited scientists and industrialists. The inventors promoted the spread of these new ideas by teaching a series of lectures on computer architecture.


Summer 1 2021
Welcome back after the Easter holidays!
Homework and Spellings will be sent home on a Monday.
Homework due on the Friday.
Spellings given on a Monday will be tested on a Friday.
P.E. will be on a Friday. P.E. kits to be named and in a named bag. P.E. will be outside again for this half term so you may want to send in a track suit to keep legs and arms warm.
We will be reading the book Return written by Aaron Becker.
We will be learning to write our own setting description using the images from the story and we will also be writing a non-fiction travel report.
Our class read is Esio Trot by Roald Dahl, after the children read The Magic Finger in the Autumn term, we are continuing getting to know the author.
We will continue with Bug Club and reading a range of texts on this site:
We will be focusing our maths learning on fractions. We will be using and understanding fraction notation, finding unit fractions of quantities, learning fractions within 1 in the linear number system, and adding and subtracting fractions within 1.
Most of you are enjoying playing TT Rockstars which is an interactive mental maths resources that will help you recall multiplication and division facts. Please keep going!
The Hit the Button link attached can also help with this.
This half term our Geography topic is learning about Mountains, Volcanoes and Earthquakes.
We are going to learn about how volcanoes are formed and the impact that volcanoes and earthquakes can have around the earth.
Can you name the two types of volcanoes?
For science this half term we will be learning about how plants grow and what they need in order to grow. We will be observing plants growing over time and applying our maths skills to measure and record the growth of plants.
Light, space, soil, water, nutrients, air, fertiliser, growth, volume, comparative
Year 3 Class Teacher
Year 3 Teaching Assistant