The Fast N' Hot food chain wants to test if their "Buy One, Get One Free" program
increases customer traffic enough to support the cost of the program. For each of 15
stores, one day is selected at random to record customer traffic with the program in
effect, and one day is selected at random to record customer traffic with program
not in effect. The results of the experiment are documented in DATA. For each store,
compute difference = traffic with program minus traffic without program. At $\alpha$ =
0.05, test the hypothesis that the mean difference is at most 0 (at best the program
makes no difference, or worse it decreases traffic) against the alternative that the
mean difference > 0 (the program increases traffic).
The pvalue of 0.221 indicates that the data provide insignificant evidence
against HO. HO is not rejected at $\alpha$ = 0.05. You decide to conclude the study and
not to recommend the program.
The pvalue of 0.033 provides strong evidence against HO. HO is rejected at $\alpha$ =
0.05. You decide to recommend further evaluation of the program.
The pvalue of 0.002 provides overwhelming evidence against HO. HO is rejected
at $\alpha$ = 0.05. You decide that the program results in increased customer traffic,
overall, and recommend the program be implemented.
The pvalue of 0.084 provides weak evidence against HO. HO is not rejected at $\alpha$
= 0.05. You decide the evidence is not strong enough to recommend further