1. Confidence Intervals Chapter 10

2. Confidence Intervals: The Basics Section 10.1

3. Points to Remember

4. Example: IQ and Admissions

5. Confidence Intervals Confidence Interval: estimates the value of a population parameter Confidence level: actual number percentage of confidence

6. 1. The data come from an SRS from the population of interest

7. One Sample z-interval for a Population Mean

8. Constructing Confidence Intervals

9. How can you reduce your margin of error?

10. Choosing the Sample Size for a desired margin of error

11. Estimating a Population Mean Section 10.2

12. Points to Remember

13. Standard Error

15. One Sample t - Interval

17. Use the 4 Steps

18. Step 4: Conclude: We are 90% confident that the interval from 292.32 to 320.32 mV captures the true mean tension in the entire batch of video terminals produced that day.

19. Robust Procedures  An inference procedure is called robust if the probability calculations involved in that procedure remain fairly accurate when a condition for use of the procedure is violated.  Changing things such as normality, randomness, and independence doesn’t change the data, then the inference procedure is robust  t procedures are not robust against outliers

20. Using the t Procedures

21. Estimating a Population Proportion Section 10.3

22. Points to Remember

23. Confidence Interval for a Population Proportion

24. Teens Say Sex Can Wait The Gallup Youth Survey asked a random sample of 439 U.S. teens aged 13 to 17 whether they thought young people should wait to have sex until marriage. Of the sample, 246 said “Yes”. Construct and interpret a 95% confidence interval for the proportion of all teens who would say “Yes” if asked this question. STATE: We want to estimate the actual proportion p of all 13 to 17 year- olds in the United States who would say that young people should wait to have sex until they get married at a 95% confidence interval.

26. Sample Size for a Desired Margin of Error