Chapter 10: Introduction to Inference
Key Vocabulary:
§ confidence interval § margin of error § interval § confidence level § a level C confidence interval § upper p critical value § test of significance § null hypothesis § alternative hypothesis § pvalue

§ statistically significant § test statistic § significance level § z test statistic
§
Hawthorne
effect
§ Type I Error § Type II Error § acceptance sampling § power (of a test)

Calculator Skills:
§ ZInterval
§ ZTest
10.1 Estimating with Confidence (pp.536559)
1. In statistics, what is meant by a 95% confidence interval?
2. Sketch and label a 95% confidence interval for the standard normal curve.
3. In a sampling distribution of , why is the interval of numbers between called a 95% confidence interval?
4. Define a level C confidence interval.
5. Sketch and label a 90% confidence interval for the standard normal curve.
6. What does z* represent?
7. What is the value of z* for a 95% confidence interval? Include a sketch.
8. What is the value of z* for a 90% confidence interval? Include a sketch.
9. What is the value of z* for a 99% confidence interval? Include a sketch.
10. What is meant by the upper p critical value of the standard normal distribution?
11. Explain how to find a level C confidence interval for an SRS of size n having unknown mean m and known standard deviation s.
12. What is meant by a margin of error?
13. Why is it best to have high confidence and a small margin of error?
14. What happens to the margin of error as z* decreases? Does this result in a higher or lower confidence level?
15. What happens to the margin of error as s decreases?
16. What happens to the margin of error as n increases? By how many times must the sample size n increase in order to cut the margin of error in half?
17. The formula used to determine the sample size n that will yield a confidence interval for a population mean with a specified margin of error m is . Solve for n.
10.2 Tests of Significance (pp.559585)
1. What is a null hypothesis?
2. What is an alternative hypothesis?
3. In statistics, what is meant by the Pvalue?
4. If a Pvalue is small, what do we conclude about the null hypothesis?
5. If a Pvalue is large, what do we conclude about the null hypothesis?
6. How small should the Pvalue be in order to claim that a result is statistically significant?
7. Explain the difference between a onesided alternative hypothesis and a twosided alternative hypothesis.
8. What does a test statistic estimate?
9. What is meant by a significance level?
10.3 Using Significance Tests (pp.560566)
10.4 Inference as Decision (pp. 567577)
1. Significance tests are not always valid.
What are some factors that can invalidate a test?
2. Explain the difference between a Type I Error and a Type II Error.
3. What is the relationship between the significance level a and the probability of Type I Error?
4. Describe how to calculate the power of a significance test.