Central Limit Theorem - Sampling Distribution of Sample Means - Stats & Probability

This statistics video tutorial provides a basic introduction into the central limit theorem. It explains that a sampling distribution of sample means will form the shape of a normal distribution regardless of the shape of the population distribution if a large enough sample is taken from the population. This video gives plenty of examples and practice problems. Here is a list of topics: 0:00 - An Introduction To The Central Limit Theorem 2:55 - The Sampling Distribution of the Sample Mean 5:52 - Basic Review of Statistical Symbols 7:57 - The Law of Large Numbers 11:19 - The Z-Score Formula For Sampling Distributions 12:54 - The Relationship Between Sample Size and Standard Error 15:31 - The Uniform Distribution Review 17:50 - The Exponential Distribution Review 20:25 - The Normal Distribution vs The Sampling Distribution 23:58 - Probability Problems 32:33 - How To Find The 80th Percentile of a Sampling Distribution 34:43 - Probability Problems With Uniform Distribution & Sampling Distribution of the Sample Mean 46:06 - Sampling Distribution of Sample Sum 51:18 - Probability Problems With Exponential Distribution 55:26 - Finding The IQR of a Sampling Distribution My Website: https://www.video-tutor.net Patreon Donations: https://www.patreon.com/MathScienceTutor Amazon Store: https://www.amazon.com/shop/theorganicchemistrytutor Subscribe: /channel/UCEWpbFLzoYGPfuWUMFPSaoA Disclaimer: Some of the links associated with this video may generate affiliate commissions on my behalf. As an amazon associate, I earn from qualifying purchases that you may make through such affiliate links.

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