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 8

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Lecture 8 - Confidence Intervals
Suppose you are trying to determine the average rent of a two-bedroom apartment in your town. You might look in the classified section of the newspaper, write down several rents listed, and average them together. You would have obtained a point estimate of the true mean. If you are trying to determine the percent of times you make a basket when shooting a basketball, you might count the number of shots you make and divide that by the number of shots you attempted. In this case, you would have obtained a point estimate for the true proportion. We use sample data to make generalizations about an unknown population. This part of statistics is called "inferential statistics." The sample data help us to make estimates of population parameters. We realize that the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct confidence intervals in which we believe the parameter lies. This lecture covers how to construct and interpret confidence intervals. You will also learn a new distribution, the Student-t, and how it is used with these intervals.
Dr. Barbara Illowsky, Susan Dean
Collaborative Statistics (Connexions) http://cnx.org Date accessed: 2009-01-17 License: Creative Commons Attribution 2.0 |