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 Answer the following questions about interpreting p-values. 14. Suppose that the null hypothesis is, “The population mean is \$200,” and the alternative hypothesis is, “The population mean is less than \$200.” Also, suppose the test statistic value is -0.50, with a p-value of 0.31. The p-value is the probability ofA) obtaining our test statistic value or a value even smaller, if in fact the population mean is less than \$200B) obtaining our test statistic value or a value even larger, if in fact the population mean is less than \$200C) obtaining our test statistic value or a value even smaller, if in fact the population mean is \$200D) obtaining our test statistic value or a value even larger, if in fact the population mean is \$20015. Suppose that the null hypothesis is, “The population proportion is 0.50,” and the alternative hypothesis is, “The population proportion is greater than 0.50.” Further, suppose that our test statistic is +1.96, with a p-value of 0.025. The p-value is the probability ofA) obtaining our test statistic value of 1.96 or larger, if in fact the population proportion is 0.50B) obtaining our test statistic value of 1.96 or smaller, if in fact the population proportion is 0.50C) obtaining our test statistic value of 1.96 or larger, if in fact the population proportion is greater than 0.50D) obtaining our test statistic value of 1.96 or smaller, if in fact the population proportion is greater than 0.5016. A p-value of 0.05 or less is said to indicate that the results are “statistically significant.” What does statistically significant mean?A) The null hypothesis is a poor explanation of the data.B) The null hypothesis is a good explanation of the data.C) The alternative hypothesis is a poor explanation of the data.17. Three of the following statements about a p-value are true. Which one is false?A) If we got a p-value of 0.52, we would not reject the null hypothesis.B) If the p-value is very small, we reject the null hypothesis.C) The p-value is the probability that the null hypothesis is true.D) The p-value is the probability, assuming the null hypothesis is true, of seeing results as (or more) extreme as what we observed in the sample.

14) C) obtaining our test statistic value or a value even smaller, if in fact the population mean... View the full answer

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