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Data: https://docs.google.com/spreadsheets/d/1doVB7flHFX-zSCEQJcY4mx73avy195QpSMp1CmvipDs/edit?usp=sharing (Copy to excel to .csv) The NFL is concerned with television viewership and is considering an arrangement with the networks regarding the price

Data: https://docs.google.com/spreadsheets/d/1doVB7flHFX-zSCEQJcY4mx73avy195QpSMp1CmvipDs/edit?usp=sharing (Copy to excel to .csv)

The NFL is concerned with television viewership and is considering an arrangement with the networks regarding the price they pay to broadcast games. If the proportion of "blowout" games is below (in a statistically significant way) 0.5, then the NFL will be paid a bonus by the networks. Similarly, if the proportion of "close" games is above 2/9 (in a statistically significant way), then the NFL is paid a bonus by the networks.

a. We will say that a game is a blowout if the game is won by more than 8 points. Add the variable Diff to the data set by using the below command. This variable will give the amount that the home team won by (if Diff > 0) or lost by (if Diff <0).

data$Diff<-data$score1-data$score2

Next, use the command

B<-sum(data$Diff>8,data$Diff<(-8))

to find the number of blowout games in the data set.

b. Calculate the test statistic for the hypothesis test that will determine if the proportion of blowout games is significantly less than 0.5.

c. What is the result of the hypothesis test? Why?

d. We will say that a game is close if the game is won by 3 or fewer points. Amend the code in part a to find the number of close games in the data set.

e. Calculate the test statistic for the hypothesis test that will determine if the proportion of close games is significantly more than 2/9.

f. What is the result of the hypothesis test? Why?

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