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Are you here?. Yes, and I’m ready to learn Yes, and I need a nap No. HW - Problem 6. When a truck load of apples arrives at a packing plant, a random sample of 125 is selected and examined for bruises, discoloration, and other defects.

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  1. Are you here? • Yes, and I’m ready to learn • Yes, and I need a nap • No

  2. HW - Problem 6 • When a truck load of apples arrives at a packing plant, a random sample of 125 is selected and examined for bruises, discoloration, and other defects. • The whole truckload will be rejected if more than 5% of the sample is unsatisfactory. • Suppose that in fact 9% of the apples on the truck do not meet the desired standard. • What is the probability that the shipment will be accepted anyway.

  3. What is the probability that the shipment will be accepted anyway? • 0.059 • 1-0.059 • 0 • 1 • .05

  4. Chapter 19 Confidence Intervals for Proportions

  5. Exciting Statistics about ISU Students • 71% of sexually active students use condoms • American College Health Association • n=706

  6. A Confidence Interval

  7. Consider the 95% level: There’s a 95% chance that p is no more than 2 SEs away from . So, if we reach out 2 SEs, we are 95% sure that p will be in that interval. In other words, if we reach out 2 SEs in either direction of , we can be 95% confident that this interval contains the true proportion. This is called a 95% confidence interval. A Confidence Interval

  8. By the 68-95-99.7% Rule, we know about 68% of all samples will have ’s within 1 SE of p about 95% of all samples will have ’s within 2 SEs of p about 99.7% of all samples will have ’s within 3 SEs of p A Confidence Interval

  9. What Does “95% Confidence” Really Mean? • Each confidence interval uses a sample statistic to estimate a population parameter. • But, since samples vary, the statistics we use, and thus the confidence intervals we construct, vary as well.

  10. What Does “95% Confidence” Really Mean? (cont.) • The figure to the right shows that some of our confidence intervals capture the true proportion (the green horizontal line), while others do not:

  11. What Does “95% Confidence” Really Mean? (cont.) • Thus, we expect 95% of all 95% confidence intervals to contain the true parameter that they are estimating. • Our confidence is in the process of constructing the interval, not in any one interval itself.

  12. Homework Problem • A catalog sales company promises to deliver orders placed on the Internet within 3 days. • Follow-up calls to a few randomly selected customers show that a 95% CI for the proportion of all orders that arrive on time is 81% ± 4%

  13. Which of the following statements is correct? • Between 77% and 85% of all orders arrive on time. • One can be 95% confident that the true population percentage of orders place on the Internet that arrive within 3 days is between 77% and 85% • One can be 95% confident that all random samples of customers will show that 81% of orders arrive on time • 95% of all random samples of customers will show that between 77% and 85% of orders arrive on time.

  14. Certainty vs. Precision

  15. Certainty vs. Precision • The choice of confidence level is somewhat arbitrary, but keep in mind this tension between certainty and precision when selecting your confidence level. • The most commonly chosen confidence levels are 90%, 95%, and 99% (but any percentage can be used).

  16. When the conditions are met, we are ready to find the confidence interval for the population proportion, p. The confidence interval is where The critical value, z*, depends on the particular confidence level, C, that you specify. One-Proportion z-Interval

  17. Z* is the Critical Value • 80%  z*=1.282 • 90% z*=1.645 • 95% z*=1.96 • 98%z*=2.326 • 99% z*=2.576

  18. Critical Values (cont.) • Example: For a 90% confidence interval, the critical value is 1.645:

  19. HW – Problem 18 • Often, on surveys there are two ways of asking the same question. • 1) Do you believe the death penalty is fair or unfairly applied? • 2) Do you believe the death penalty is unfair or fairly applied?

  20. HW – Problem 18 • Survey • 1) n=597 • 2) n=597 • For the second phrasing, 45% said the death penalty is fairly applied.

  21. Suppose 54% of the respondents in survey #1 said the death penalty was fairly applied. Does this fall within a 95% confidence interval for survey #2? • Yes, it falls within my CI • No, it does not fall within my CI

  22. Margin of Error: Certainty vs. Precision • We can claim, with 95% confidence, that the interval contains the true population proportion. • The extent of the interval on either side of is called the margin of error (ME). • In general, confidence intervals have the form estimate± ME. • The more confident we want to be, the larger our ME needs to be.

  23. Margin of Error - Problem • Suppose the truth is that 56% of ISU student drink every weekend. • We want to create a 95% confidence interval, but we also want to be as precise as possible. • How many people should we sample? • How large should our margin of error be?

  24. How many people should we sample to get a ME of 1%? • 1,000 • Between 1,000 and 4,000 • Between 4,000 and 8,000 • Between 8,000 and 16,000

  25. Margin of Error: Certainty vs. Precision • The more confident we want to be, the larger our z* has to be • But to be more precise (i.e. have a smaller ME and interval), we need a larger sample size, n.

  26. Upcoming work • Quiz #4 in class today • HW #8 due next Sunday • Part 3 of Data Project due Oct. 29

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