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Question

To combat red-light-running crashes, many states are installing red light cameras at dangerous intersections. These cameras photograph the license plates of vehicles that run red lights and automatically issue tickets. How effective are these photo enforcement programs? The Virginia Department of Transportation (VDOT) conducted a comprehensive study of its newly adopted program and published the results in a 2012 study. In one portion of the study, VDOT provided crash data both before and after installation of the cameras at several intersections. The data, measured as the crash rate caused by red light running per intersection per year, for 13 randomly selected intersections in Fairfax County are given in the first columns in the StatCrunch file.

Data from Statcrunch:

C) At the 0.01 significance level, test the claim that the installation of the cameras decreased the mean number of crashes at intersections where the cameras were installed.

i.State the null and alternative hypotheses.

ii.State the significance level for this problem.

iii.Calculate the test statistic (subtract after – before)

iv.Calculate the P-value and include the probability notation statement.

v.State whether you reject or do not reject the null hypothesis.

vi.State your conclusion in context of the problem (i.e. interpret your results).

D) For the above situation, construct a 96.2% confidence interval for the above data. Interpret the confidence interval as we learned in class. Verify your interval using StatCrunch

Note: For part d, to earn full credit, show how you obtained the critical value for the confidence interval in StatCrunch. Then, write out the confidence interval formula you would use, and the steps necessary to construct the confidence interval.

I just need the answer for D. I\'m struggling how to find the T Critical Value. Please use any technology if you like.

Solution