Excel Statistical Analysis 37: Learn Central Limit Theorem by Building Sampling Distribution of Xbar

Learn about one of the most power rules in statistics: the Central Limit Theorem by building a Sampling Distribution of Sample Means (Xbar). Learn how to calculate the Mean and Standard Deviation (Standard Error) for the Sampling Distribution of Sample Means (Xbar). Then see how the Central Limit Theorem is used to make business decisions using Hypothesis Testing, Confidence Intervals and the Excel worksheet functions NORM.DIST, NORM.S.DIST, NORM.S.INV and T.INV. Learn about the z distribution and the t distribution as models to represent the Sampling Distribution of Sample Means (Xbar) to help make business decisions.
Topics:
1. (00:00) Introduction
2. (01:00) Building a Sampling Distribution of Sample Means (Xbar)
3. (02:43) XLOOKUP to lookup all values for all possible samples.
4. (03:39) Proving that Mean of Sampling Distribution of Sample Means (Xbar) is equal to Population Mean
5. (05:53) Build Frequency Distribution & Histograms using worksheet formulas. See SEQUENCE and COUNTIFS functions to discover that the pattern for the Sampling Distribution of Sample Means (Xbar) is Normal, or Bell shaped
6. (13:47) Sampling Distribution of Sample Means (Xbar) has less spread than Population Data
7. (14:26) Central Limit Theorem and its use to make decisions
8. (15:52) Learning how the Standard Deviation (Standard Error) Formula is created from Sampling Distribution of Sample Means (Xbar)
9. (17:17) Standard Error Formula
10. (19:11) Correction Factor for Standard Error
11. (24:21) Relationship between Sample Size, Standard Error and the probability associated with a given interval with a lower and upper value
12. (29:42) Sampling Distribution, Normal Bell Distribution Model and the Central Limit Theorem to make business decisions
13. (31:25) First mention of t distribution
14. (31:55) Check reasonableness of a claim with two statistical methods: Hypothesis Testing and Confidence Intervals
15. (34:03) Hypothesis Testing to assess whether a claim is reasonable: Insurance Policy Price example. See Excel functions: NORM.S.DIST, NORM.S.INV
16. (39:46) Confidence Intervals to assess whether a claim is reasonable: Insurance Policy Price example
17. (41:05) Confidence Intervals to estimate a range of values for a population mean: Computer Printer Cartridge example
18. (41:57) t Distribution example. See the Excel function: T.INV
19. (45:53) Assessing reasonableness of Manufacture sample. See Excel functions: NORM.DIST and NORM.S.DIST to calculate p-value
20.
21. () Excel worksheet functions NORM.DIST, NORM.S.DIST, NORM.S.INV and T.INV
22. () z distribution as model to represent the Sampling Distribution of Sample Means (Xbar) to help make business decisions
23. () t distribution as model to represent the Sampling Distribution of Sample Means (Xbar) to help make business decisions
24. ()
25. (48:40) Summary of video
26. (49:31) Closing, Next Video and Video Links

[bamakaze]

This is the best tool and subject in statistics. Central limit theorem watch out!

[richardhay]

Great NEW video! LOL I think surveying z vs t, hypothesis test vs confidence interval and standard deviation vs standard error vs margin of error is great preparation to all that comes later.
Students should wathch this video again after these topics are explored more thoroughly. Many students will appreciate this overview now. The rest will appreciare it later.

[johnborg]

GOLD!!!! Pure GOLD!!! Thanks Mike. :) :)

[chrism]

Outstanding Thanks for all you do to make the Team better!

[darrylmorgan]

Boom!Simply An Epic Fun Class, Loving These Wicked Statistical Lessons...Thank You Mike :)

[darylseaton]

Dave, thanks for the video. Toward the end, you start dividing and multiplying terms that appear to be different that the beginning of the video. I would encourage you to slow down a bit, so that we can make the link between the different sections clear. Now, that may just be me, but that's just me.

[Al-Ahdal]

1. Boss, kindly help the community in all cube functions.
2. Advanced Formula Environment.
Thanks in advance.