Cherry Blossom Run ~ Is the typical US runner getting faster or slower over time? We consider this question in the context of the Cherry Blossom Race, which is a 10-mile race in Washington, DC each spring. The average time for all runners who finished the Cherry Blossom Race in 2006 was 93.29 minutes. We want to determine whether the average time of runners in this race has changed since 2006. Using data from 52 participants in the 2017 Cherry Blossom Race, we find the mean run time was 95.7 minutes with a standard deviation of 18.89 minutes. Round all calculated values to 4 decimal places. 1. Which test should you use to answer the research question? A. 2 goodness of fit test B. t test for sample mean C. Z test for one population proportion D. 2 test of independence 2. Which set of hypotheses should you use to answer the research question? A. H0:=93.29 vs. Ha:95.7

B. H0:=93.29 vs. Ha:93.29

C. H0:=93.29 vs. Ha:>93.29

D. H0:=95.7 vs. Ha:95.7

E. H0:=93.29 vs. Ha:<93.29

F. H0:x=95.7 vs. Ha:x95.7 3. What conditions must be met for the hypothesis test to be valid? Select all that apply:

A. The standard error must be larger than the standard deviation of the sample data.

B. The sample size must be large enough to ensure at least 10 success and failure observations under the null model.

C. The sample observations must be independent.

D. The expected value of the standard error must be at least 5.

E. The population of race times must be normally distributed or the sample size must be sufficiently large (n > 30).

4. What is the test statistic?

? = 5. You calculate a p-value of 0.361905. Which of the following are correct interpretations of the p-value? Select all that apply:

A. A p-value of 0.361905 means that, in repeated sampling, we would expect sample mean, 95.7, to be within 0.361905 of the true population mean, on average.

B. We would expect a sample mean further from 93.29 than 95.7 approximately 36.1905% of the time in repeated sampling under the null model.

C. A p-value of 0.361905 means we have little evidence against the null hypothesis.

D. A p-value of 0.361905 means that there is a 36.1905% chance that the null hypothesis is true.

6. Calculate the effect size for your hypothesis test. d^=