Study 1: Unemployment Rates in Areas Where Minimum Wages AreHigher in the Cities Than in Surrounding Suburbs City UnemploymentRates Suburb Unemployment Rates P1 P 1 = 0.069 P2 P 2 = 0.062 N1 N1 = 52 cities N2 N 2 = 56 suburbs The Z(obtained) test statistic is1.99. Using a significance level of .05, the Z(critical) is +1.645.Which of the following is the appropriate conclusion to yourhypothesis test? The difference between the unemployment rates inthe cities and the suburbs is statistically significant. Thedifference between the unemployment rates in the cities and thesuburbs is not statistically significant. Suppose you conduct asecond study and ask half as many people the same question. Supposethe proportions remain approximately the same. The new results areshown in the following table: Study 2: Unemployment Rates in AreasWhere Minimum Wages Are Higher in the Cities Than in SurroundingSuburbs City Unemployment Rates Suburb Unemployment Rates P1 P 1 =0.068 P2 P 2 = 0.061 N1 N 1 = 26 cities N2 N 2 = 28 suburbs Whencompared with the first study, you would expect the Z(obtained)test statistic to and the Z(critical) to . Without computing thetest statistic for the second study, you your conclusion will bethe same as your conclusion for the first study. Now that you havea sense of how changing the sample size affects the statisticalsignificance of the statistical finding, what about whether thetest is one-tailed or two-tailed? How does moving from a one-tailedtest to a two-tailed test change the probability of rejecting thenull hypothesis? The probability of rejecting the null hypothesisdoes not change. The probability of rejecting the null hypothesisdecreases. The probability of rejecting the null hypothesisincreases. How does changing the sample size, or changing fromone-tailed to two, affect the importance of the statisticalfinding? Check all that apply. Sample size does not affect theimportance of a statistical finding. Changing from two-tailed toone is more likely to produce a statistically significant finding,but that doesn't mean it will be more important. A small sample ismore likely to result in an important statistical finding. A largesample is more likely to result in an important statisticalfinding.