© 2013 Pearson Education, Inc. Active Learning Lecture Slides For use with Classroom Response Systems Introductory Statistics: Exploring the World through Data, 1e by Gould and Ryan Chapter 7.5 Survey Sampling and Inference Slide 7 - 1

In most situations in the “real world,” we know the value of the population proportion A. True B. False Slide © 2013 Pearson Education, Inc. Response Counter

Statistical inference is the art and science of drawing conclusions about a population on the basis of observing only a small subset of that population. A. True B. False Slide © 2013 Pearson Education, Inc. Response Counter

A confidence interval provides a range of plausible values for a population parameter. A. True B. False Slide © 2013 Pearson Education, Inc. Response Counter

A confidence interval is often reported as an estimate plus or minus some amount. This “some amount” is called A. Confidence level B. Capture rate C. Margin of error D. Standard error Slide © 2013 Pearson Education, Inc. Response Counter

The confidence level measures A. The probability of the parameter being contained in the interval B. How often the estimation method is successful C. The probability of a statistic being contained in the interval. D. All of the above. Slide © 2013 Pearson Education, Inc. Response Counter

True or False The confidence level measures the capture rate for our method of finding confidence intervals. A. True B. False Slide © 2013 Pearson Education, Inc. Response Counter

True or False It is correct to say that a particular confidence interval has a 95% (or any other percent) chance of including the true population parameter. A. True B. False Slide © 2013 Pearson Education, Inc. Response Counter

True or False It is correct to say that the process that produces intervals captures the true population parameter with a 95% probability. A. True B. False Slide © 2013 Pearson Education, Inc. Response Counter

To obtain a 95% confidence level, we use a margin of error of A standard errors B standard errors C standard errors D standard errors Slide © 2013 Pearson Education, Inc. Response Counter

In the 1960 presidential election, 34,226,731 people voted for Kennedy; 34,108,157 for Nixon, and 197,029 for third- party candidates. Would it be appropriate to find a confidence interval for the proportion of voters choosing Kennedy? A. Yes, simple find the standard error and add/subtract 1.96 times the standard error to the estimate. B. No, we already know the population proportion. We only need a confidence interval when we have a sample proportion and want to generalize about the population. Slide © 2013 Pearson Education, Inc. Response Counter