# Chapter 9: Sampling Distributions_

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## Introduction

Length: 53 minutesAuthor: Jason Random samples should act in a random (unpredictable) way... right? WRONG! As samples grow in size, the probability of randomly selecting samples with specific means becomes easier and easier to predict. I show how this is the logical result of the Central Limit Theorem using an easy to follow example.

## 2 | Comparing Chapters 9 and 8

Length: 32 minutesAuthor: Jason Chapters 8 and 9 both ask probability questions, they both work with continuous data, and they both rely on standard normal tables for finding probabilities - So how do we know when to use Chapter 9 techniques? It comes down to sample sizes and working with averages...

## 3 | Probability of a Sample Mean

Length: 9 minutesAuthor: Jason Some questions ask for the probability that the sample mean falls within a given range. The opposite is also asked: Which sample mean occurs with a given probability? To solve this, we just need to reverse the order of some of the steps in our solution.

## 4 | Binomial vs. Sample Proportions

Length: 22 minutesAuthor: Jason Some questions can be solved by the techniques in more than one chapter. There is a significant overlap between Chapter 7 binomial and Chapter 9 sample proportions. Both teach you how to find the probabilities of multiple nominal (binomial) outcomes. I explain here how Ch.9 sampling distributions can (sometimes) be the easiest way to solve a binomial problem.

## Comparing 2 Populations

Length: 17 minutesAuthor: Jason The math in this kind of problem looks horrible, but I'll show you how we can find the probability of a difference in sample means quickly using the same simple steps that have worked throughout the rest of the chapter.

## Multiple Choice

Author: Jason Test your understanding of Chapter 9: Sampling Distributions - each question is accompanied by a mini-video lecture showing you how I decided which solution was the correct one.