Lectures (Video)

- 1. Sampling and Data
- 2. Descriptive Statistics
- 3. Probability Topics
- 4. Discrete Distributions
- 5. Continuous Random Variables
- 6. The Normal Distribution
- 7. The Central Limit Theorem
- 8. Confidence Intervals
- 9. Hypothesis Testing - Single Mean and Single Proportion
- 10. Hypothesis Testing - Two Means, Two Proportions, Paired Data
- 11. The Chi-Square Distribution
- 12. Linear Regression and Correlation

## Introduction to Statistics II - Lecture 11

Get the Flash Player to view video.
Lecture 11 - The Chi-Square Distribution
Have you ever wondered if lottery numbers were evenly distributed or if some numbers occurred with a greater frequency? How about if the types of movies people preferred were different across different age groups? What about if a coffee machine was dispensing approximately the same amount of coffee each time? You could answer these questions by conducting a hypothesis test. You will now study a new distribution, one that is used to determine the answers to the above examples. This distribution is called the Chi-square distribution. This lecture covers the three major applications of the Chi-square distribution: - - The goodness-of-fit test, which determines if data fits a particular distribution, such as with the lottery example
- - The test of independence, which determines if events are independent, such as with the movie example
- - The test of a single variance, which tests variability, such as with the coffee example
Dr. Barbara Illowsky, Susan Dean
Collaborative Statistics (Connexions) http://cnx.org Date accessed: 2009-01-17 License: Creative Commons Attribution 2.0 |