Advanced Statistics functions in EXCEL 2010-2013 (Part 2)

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Learn how to use advanced statistics functions in EXCEL 2010 and 2013 to effectively analyze data.

288 students enrolled

What Will I Learn?

- After completing this course, you will feel comfortable using EXCEL 2010-2013 advanced statistical functions for Analytics and Applied Statistical analyses.
- In this course, you will learn advanced statistical functions about the Normal or Bell-Shaped distribution, Student t distribution, chi square, lognormal, negative binomial, etc..
- You will effectively be able to solve inferential statistical problems using the functions you studied and feel comfortable using the power of EXCEL advanced statistical function for analyses.

Requirements

- EXCEL 2010, 2013 or HIGHER

Description

**Updated material to include latest advanced Statistical functions in EXCEL 2013**This course has been updated to include the latest advanced statistical functions in EXCEL 2013. It provides you with a vast array of analytical tools to handle most

The course is about using the advanced statistical functions in EXCEL for data analysis and analytics projects.

You will learn how to effectively use **Advanced Excel Statistical Functions** about the Normal distribution, Student-t distribution, chi square distribution, F distribution, Gamma, Log-normal, Negative Binomial, Exponential, etc.

You will learn how to calculate the margin of errors and use them to create confidence intervals. In addition, you will learn how to create Standard Normal tables as well as Student t tables.

This course is very well illustrated with lots of practical illustrations and quizzes to help you grasp the concepts of each function and understand them in a practical way. Excel files and screenshots are provided to make the understanding of the lectures very easy.

Depending on the prior preparation, this course can be completed in one month or less. **Taking this course** will provide you with a rich array of advanced analytical tools that can be used for educational and professional work.

Who is the target audience?

- College students taking statistics classes and interested in using EXCEL advanced statistical functions for their projects
- Anyone involved with analytics, applied statistics or using statistical capability of EXCEL 2010-2013 to analyze data
- Anyone involved with analytics, applied statistics or interested in using the statistical capability of EXCEL to analyze data

Compare to Other Excel Courses

Curriculum For This Course

44 Lectures

02:46:28
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Welcome to Statistical functions in EXCEL 2010 (Part 2 -Intermediate and Advanced)
2 Lectures
09:48

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Functions related to the normal or bell-shaped distribution
9 Lectures
46:08

In this video, we are computing standard normal distributions probabilities. This is equivalent to reading the Standard Normal Z table for finding probabilities, except that here, EXCEL computes it directly for us.

Finding the standard normal distribution probabilities

06:27

In this video, we learn how to compute probabilities about a Normal distribution with a given mean and standard deviation.

Preview
07:09

In this lesson, we learn how to solve problems related to the inverse of the stand normal distribution. For example, if the weights of pygmy goats are normal with a mean of 80 pounds and standard deviation of 3.5 pounds, what goat weight corresponds to the 95th percentile?

Finding the inverse of a normal distribution

04:55

In this lesson, we are calculating inverse or Z-value of a standard normal distribution. For example, what is the Z value corresponding to the 90th percentile of the standard normal distribution?

Find the inverse (Z-value) of the standard normal distribution

03:01

In this lesson, we use the standard normal density function to create a bell-shaped curve. This curve comes in handy if you want to show how the bell-shaped distribution looks like.

How to plot the standard normal distribution curve

07:35

In this video, we use built-in standard normal distribution functions to create a standard normal table. The table can be printed and used in lieu of the tables in statistical books.

Creating a standard normal distribution table

07:19

This video shows how to compute the Z values or standardize the data in EXCEL 2010

How to standardize by computing the Z value

01:39

In this lesson we show how to use a Z-test function to test an hypothesis about the population mean assuming a normal distribution.

Using a Z-test to test an hypothesis about the population mean

04:39

In this video, we show that the function CONFIDENCE.NORM computes the margin of error for a large sample size confidence interval about the population mean assuming a normal distribution.

Computing the margin of error for a large sample size confidence interval about the population mean

03:24

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Functions related to the Student t distribution
8 Lectures
27:13

Finding the left tailed P-value for testing an hypothesis about a population mean using Student T.DIST function

Obtaining a left-tailed P-value about the population mean with T.DIST

02:54

In this lesson, we show how to find a critical Student t value corresponding to a left tailed test of hypothesis about the population mean

Finding the critical table value corresponding to a left-tailed student t distribution

02:19

In this video, we show how to find the critical value corresponding to a two tailed test using Student t test

Finding the critical table value corresponding to a two-tailed t distribution

02:26

In this video, we show how to find a right-tailed P-value for a Student t test.

Finding the right-tailed P-value using for testing a population mean using Student t distribution

03:17

Finding a two-tailed P-value when testing an hypothesis about the population mean using Student t distribution

Finding a two-tailed P-value when testing an hypothesis about the mean using Student t distribution

02:11

In this video, we show How to create a Student t table using EXCEL Student t function

Creating a Student t table with a T.INV function

05:36

In this lesson, we show how to test an hypothesis about two populations means using Student t test. We provide detailed explanation for the test.

Testing hypothesis about two populations means using Student t-test

03:33

In this video, we are calculating the Margin of Error corresponding to a small sample size confidence interval for the population mean using Student t distribution.

Computing the margin of error for estimating a population mean using Student t distribution

04:57

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Computing Chi-square distribution probabilities and critical values
5 Lectures
16:39

In this lesson, we show how to find the left tailed P-value of a chi square distribution. This is important when we are testing an hypothesis with a left tailed test.

Finding the left-tailed P-value for testing an hypothesis about the population variance using chi.dist

03:09

In this lesson, we show how to find the right tailed P-value of a chi square distribution which is used to decide about statistical hypotheses.

Finding the right-tailed P-value for testing an hypothesis about a population variance using the Ch square distribution

02:30

In this video, we are finding the critical tables values corresponding to a chi square left tailed test

Finding the critical table value for testing a left-tailed hypothesis about a population variance using Chi Square distribution

03:16

In this lesson, we show how to find the critical tables values corresponding to a chi square right tailed test

Find the critical table value for testing a right-tailed hypothesis about a population variance using the Chi square distribution

02:27

In this lesson, we show how to conducte a test of chi square test of independence using the chi square test

Testing an hypothesis of independence using the Chi square test

05:17

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Computing F-Distribution probabilities
4 Lectures
12:16

In this lesson, we show how to find the left tailed P-value with F.DIST function

Computing a left-tailed P-value for testing the equality of two population variances using the F distribution

03:06

In this video, we show how to find the right tailed P-value of the F distribution

Computing a right-tailed P-value for testing the equality of two populations variances using the F-distribution

03:17

In this lesson, we show how to find the right tailed critical value of an F distribution

Finding a right-tailed critical value for testing two variances using the F.INV.RT

04:08

In this lesson, we show how to test that two populations variances are equal with the FTEST function. This step is necessary for those who want to test the equality of two populations means.

Testing equality of two populations variances with the F-test

01:45

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Other advanced Statistical functions in EXCEL 2010
8 Lectures
25:15

In this lesson, we show how to use the exponential distribution in practice. The exponential distribution is used to model waiting time probabilities.. Example: How long will we have to wait until a customer arrives at a toll booth?How long will machinery work without needing repair?

Computing Exponential distribution probabilities

02:04

In this video, we show how to fit the exponential growth model to data that appears to have an expontential growth and then make future forecasts.

Fitting exponential growth models to data with the growth function

05:25

We show in this video how to use the Gamma distribution, another waiting time model to compute probabilities. It is used in marketing, insurance risk, economics, meteorology, etc..

Evaluating Gamma distribution probabilities

02:30

In this video we show how to use the GammaLN function to compute factorials of numbers

Computing factorials with the Gamma related functions

03:49

In this video, we show how to compute probabilities about the negative binomial for solving a real world problem. It returns the probability that there will be a given number of failures before the rth success. The geometric distribution is a special case of of the Negative Binomial. It is defined as the num.ber of trials (failures) until the 1st success

Computing probabilities of the Negative binomial distribution

03:34

In this video, we show how to use the lognormal distribution, which is a distribution where the ln(x) is normally distributed. It is sometimes called the Cobb–Douglas function in business.

Using the Log normal distribution function to compute probabilities

02:26

In this video, we show how to compute the inverse of the log normal distribution which is a distribution where the ln(x) is normally distributed. It is sometimes called the Cobb–Douglas function in business.

Finding the inverse of Log normal distribution

03:08

In this video, we show how to compute probabilities of the Weibull distribution. It is extensively used in the field of reliability engineering for measuring component lifetime.

Using the Weibull distribution to compute probabilities

02:19

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Advanced Statistical functions in EXCEL 2013
4 Lectures
12:50

In the lecture we talk about the new advanced statistical functions introduced in EXCEL 2013

Advanced new statistical functions in EXCEL 2013

02:20

This lecture explains the use of the newly introduced function Gamma function in EXCEL 2013 to evaluate the gamma of the numbers that are greater or equal to one.

Using the new Gamma function in EXCEL 2013

02:18

In this lecture, we illustrate how to use the Gauss function to evaluate standard normal distribution probabilities.

Using the new Gauss function in EXCEL 2013

04:13

This lecture explains how to use PHI function in EXCEL 2013 to evaluate the density of the standard normal distribution.

Using the PHI function in EXCEL 2013

03:59

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Practice project files and Quizzes
3 Lectures
00:00

Exercises with solutions to reinforce the understanding of the concepts

Project and practice files

8 pages

Solving problems using the normal distribution (Part1)

2 questions

Find probabilities under the standard normal distribution

2 questions

Finding the left tailed P-value for a Student t distribution

1 question

Finding the right-tailed P-value for a Student t distribution

1 question

Finding the two tailed P-value for a Student t distribution

1 question

Finding the Z values of the standard normal distribution using (alpha over 2)

Practice using the inverse of the standard normal distribution

3 pages

Finding the Student t values used in confidence interval for a given alpha and sample size n

Finding the inverse of the Student t distribution

3 pages

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Closing remarks and follow up
1 Lecture
02:19

Thank you and closing remarks

Closing remarks and suggestions

02:19

About the Instructor