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

Learn how to use advanced statistics functions in EXCEL 2010 and 2013 to effectively analyze data.
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  • Lectures 44
  • Contents Video: 2.5 hours
    Other: 14 mins
  • Skill Level Intermediate Level
  • Languages English
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About This Course

Published 3/2013 English

Course 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.

What are the requirements?

  • EXCEL 2010, 2013 or HIGHER

What am I going to get from this course?

  • 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.

What 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

What you get with this course?

Not for you? No problem.
30 day money back guarantee.

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Lifetime access.

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Desktop, iOS and Android.

Get rewarded.
Certificate of completion.

Curriculum

Section 1: Welcome to Statistical functions in EXCEL 2010 (Part 2 -Intermediate and Advanced)
03:51
Introduction about the class and me
05:57
Learning the main window interface and inserting functions
Section 2: Functions related to the normal or bell-shaped distribution
06:27
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.
07:09
In this video, we learn how to compute probabilities about a Normal distribution with a given mean and standard deviation. 
04:55
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?  
03:01
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?
07:35
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.
07:19
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.
01:39
This video shows how to compute the Z values or standardize the data in EXCEL 2010
04:39
In this lesson we show how to use a Z-test function to test an hypothesis about the population mean assuming a normal distribution.
03:24
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.
Section 3: Functions related to the Student t distribution
02:54
Finding the left tailed P-value for testing an hypothesis about a population mean using Student T.DIST function
02:19
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 
02:26
In this video, we show how to find the critical value corresponding to a two tailed test using Student t test
03:17
In this video, we show how to find a right-tailed P-value for a Student t test.
02:11
Finding a two-tailed P-value when testing an hypothesis about the population mean using Student t distribution
05:36
In this video, we show How to create a Student t table using EXCEL Student t function
03:33
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.
04:57
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.
Section 4: Computing Chi-square distribution probabilities and critical values
03:09
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.
02:30
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.
03:16
In this video, we are finding the critical tables values corresponding to a chi square left tailed test
02:27
In this lesson, we show how to find the critical tables values corresponding to a chi square right tailed test
05:17
In this lesson, we show how to conducte a test  of chi square test of independence using the chi square test
Section 5: Computing F-Distribution probabilities
03:06
In this lesson, we show how to find the left tailed P-value with F.DIST function
03:17
In this video, we show how to find the right tailed P-value of the F distribution 
04:08
In this lesson, we show how to find the right tailed critical value of an F distribution 
01:45
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.
Section 6: Other advanced Statistical functions in EXCEL 2010
02:04
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?
05:25
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.
02:30
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..
03:49
In this video we show how to use the GammaLN function to compute factorials of numbers
03:34
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
02:26
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.
03:08
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.
02:19

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.

Section 7: Advanced Statistical functions in EXCEL 2013
02:20

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

02:18

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.

04:13

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

03:59

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

Section 8: Practice project files and Quizzes
8 pages
Exercises with solutions to reinforce  the understanding of the concepts 
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
3 pages
Finding the Z values of the standard normal distribution using (alpha over 2)
3 pages
Finding the Student t values used in confidence interval for a given alpha and sample size n
Section 9: Closing remarks and follow up
02:19
Thank you and closing remarks

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Instructor Biography

Luc Zio, Adjunct faculty of Math and Statistics

I  have over 18 years of work experience in the field of statistics as an Applied Statistician. For the last  twelve years, I have also  been teaching undergraduate college level statistics courses at St Petersburg College.  As an Applied Statistician, I have developed over the years a strong interest in using EXCEL as a statistical tool with my classes in order to give to the students real world hands-on experience with Statistics.

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