Exercise 2 Data on household vehicle miles oi" travel (VM'I') ale compiled annually by the Federal Highway Administration. A researcher is interested in whether there is a difTerence in last yearis mean VM'l' l'or Midwestern and southern households (pm and p5). Independent randolu samples of [5 Midwestern households and [4 southern households provided the following data on last year's VM'I'. in thousands of miles: mama; [6.2, 12.9. 17.3. 141113.11, [0.8, 11.2. 111.6. l.,24.4,20.11.209.96, 15.1. 18.3 South ; 22.2, 19.2,9.3,24.,2u.2. 15s. 18.11., 12.2.2111, 16.1). 12.5. 182,228, 11.5 a. Graph the data as you see fit. Why did you choose the grapls] you did and what do they tell you? Also calculate summary statistics Ielevant to the research question. h. Perform a \"1% significanoe level two sample. t test for means assuming equal variance to address the re-waroher's question. Justify why the assumptions of the test are reawnal'yly met or describe what assumptions we. are assuming are. met. As part of this test, specify your hypotheses. calculate your test statistic. p mine and make a mnctmimt in the mntea't of the question {Hold or highlight these values in your mlutionsj. Show all steps of the count-utation and then check your computations using t.test. Assumptions: {I} [[l) Samples independently drawn from populations? {2) Normality? {3) Equal Variance? Hypotheses.- Computations.- rl'est Statistic P Value. Conchwimt: c. A confidence interval for the true difference in means AM - /s assuming equal population variances is reported as: (-3.527, 0.609). Identify the point estimate, margin of error, critical value, degrees of freedom, standard error or the estimator, and confidence level used to construct it. Discuss the relationship between your findings in b and c. Point estimate for UM - As Margin of Error Degrees of Freedom: Critical Value: Confidence Interval Level Standard Error of Estimator: Comparison between b and c findings: d. Compute the test statistic and p value for the hypotheses: Ho : PM - AS =0, HA : PM - As 70 not assuming equal population variances. You can use t.test(), but make sure you could also compute these values by hand (other than df). How does the difference in population variances assumptions change how we do the calculations in the two independent sample t test we perform