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

Dive into a comprehensive 50-minute video tutorial on the Central Limit Theorem and its application in statistical analysis using Excel. Build a Sampling Distribution of Sample Means (Xbar) to understand this powerful statistical concept. Calculate mean and standard deviation for the sampling distribution, and explore how the theorem is used in business decision-making through hypothesis testing and confidence intervals. Learn to utilize Excel functions like NORM.DIST, NORM.S.DIST, NORM.S.INV, and T.INV while examining z and t distributions as models for the Sampling Distribution of Sample Means. Apply these concepts to real-world examples, including insurance policy pricing and computer printer cartridge manufacturing. Download accompanying Excel and PDF files for hands-on practice and reference.

) Introduction.
) Building a Sampling Distribution of Sample Means (Xbar).
) XLOOKUP to lookup all values for all possible samples..
) Proving that Mean of Sampling Distribution of Sample Means (Xbar) is equal to Population Mean.
) 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.
) Sampling Distribution of Sample Means (Xbar) has less spread than Population Data.
) Central Limit Theorem and its use to make decisions.
) Learning how the Standard Deviation (Standard Error) Formula is created from Sampling Distribution of Sample Means (Xbar).
) Standard Error Formula.
) Correction Factor for Standard Error.
) Relationship between Sample Size, Standard Error and the probability associated with a given interval with a lower and upper value.
) Sampling Distribution, Normal Bell Distribution Model and the Central Limit Theorem to make business decisions.
) First mention of t distribution.
) Check reasonableness of a claim with two statistical methods: Hypothesis Testing and Confidence Intervals.
) Hypothesis Testing to assess whether a claim is reasonable: Insurance Policy Price example. See Excel functions: NORM.S.DIST, NORM.S.INV.
) Confidence Intervals to assess whether a claim is reasonable: Insurance Policy Price example.
) Confidence Intervals to estimate a range of values for a population mean: Computer Printer Cartridge example.
) t Distribution example. See the Excel function: T.INV.
) Assessing reasonableness of Manufacture sample. See Excel functions: NORM.DIST and NORM.S.DIST to calculate p-value.
) Summary of video.
) Closing, Next Video and Video Links.