## Introduction

In this chapter we will explore hypothesis testing, which involves making conjectures about a population based on a sample drawn from the population. Hypothesis tests are often used in statistics to analyze the likelihood that a population has certain characteristics. For example, we can use hypothesis testing to analyze if a senior class has a particular average SAT score or if a prescription drug has a certain proportion of the active ingredient.

A hypothesis is simply a conjecture about a characteristic or set of facts. When performing statistical analyses, our hypotheses provide the general framework of what we are testing and how to perform the test.

These tests are never certain and we can never prove or disprove hypotheses with statistics, but the outcomes of these tests provide information that either helps support or refute the hypothesis itself.

## Chapter Outline

- 8.1. Null and Alternative Hypotheses
- 8.2. p-Values
- 8.3. Significance Test for a Proportion
- 8.4. Significance Test for a Mean
- 8.5. Student's t-Distribution
- 8.6. Testing a Hypothesis for Dependent and Independent Samples

### Chapter Summary

## Summary

This chapter covers the basics of hypothesis testing: developing hypotheses, calculating test statistics and their probabilities, testing means and proportions, the Student's t-distribution, and testing a hypothesis about two samples.

### Image Attributions

## Description

## Difficulty Level:

Advanced## Tags:

## Subjects:

## Date Created:

Aug 13, 2012## Last Modified:

Dec 23, 2014**You can only attach files to None which belong to you**

If you would like to associate files with this None, please make a copy first.