For more information, please see full course syllabus of Statistics

For more information, please see full course syllabus of Statistics

## Discussion

## Study Guides

## Download Lecture Slides

## Table of Contents

## Related Books

### Introduction: Hypothesis Tests

The null hypothesis is a claim about a parameter that is assumed true until proven otherwise. If the null hypothesis is false, the data supports the alternative hypothesis.

When making a decision, there are two types of errors. A Type I error is when a true null hypothesis is rejected. A Type II error is when a false null hypothesis is not rejected.

A p-value is the chance that we obtained what we observed or something more extreme in the direction of the alternative hypothesis if the null hypothesis is true.

### Introduction: Hypothesis Tests

Lecture Slides are screen-captured images of important points in the lecture. Students can download and print out these lecture slide images to do practice problems as well as take notes while watching the lecture.

- Intro 0:00
- Two Hypotheses 0:13
- Null Hypothesis
- Alternative Hypothesis
- Example
- Example: Two Hypotheses 1:43
- Rejection and Non-Rejection Regions 3:25
- Type 1 and Type 2 Errors 5:30
- Type 1 Error
- Significance Level
- Type 2 Error
- Power of the Test
- Tails of the Test 9:29

0 answers

Post by Nick Lardner on June 8, 2012

when you are talking about two hypotheses wouldnt the null hypothesis of the first example about the hospital patients be H0:mu<or=60 and the alternative be H1:mu>60?