Question

To compare the effectiveness of a media campaign - via radio ads, billboards, and ads on social media websites - to reduce the incidence of impaired driving, a police chief inspected data from 60 randomly chosen CheckStops at varying locations. Thirty of these were before the launch of this campaign, 30 were after the media campaign had been running for a months time. Use α=0.05 for all calculations. For each CheckStop randomly chosen, the number of people charged with impaired driving was recorded:

Prior: 2, 9, 9, 7, 1, 6, 4, 10, 7, 6, 9, 8, 8, 5, 9, 5, 10, 4, 0, 9, 10, 10, 8, 0, 1, 3, 2, 6, 4, 7

After: 8, 5, 6, 5, 6, 3, 4, 4, 4, 4, 4, 5, 3, 4, 2, 5, 7, 4, 7, 6, 6, 5, 11, 4, 6, 7, 6, 7, 5, 7

Let μBefore represent the mean number of impaired driving charges at a checkstop prior to the launch of the campaign, and μAfte be the mean number of impaired driving charges at a checkstop after the campaign has been running for a month.

(a) Does this data suggest that the variation in the number of impaired driving charges before the campaign is equal to the variation in the number of impaired driving charges after the campaign has been running for a month?
From the appropriate statistical test, find the value of the test statistic. Test Statistic = ?

(b) Report the p-value of the test you ran in (a), using at least three decimals in your answer.
P-value = ?

Use Rstudio, please show me all of the code

Answer 1

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Test - stats (F) = 3.2478

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b) P-value = 0002207

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Decision = Reject Ho