Question

For this lab we will use NFL Scouting Combine data for drafted running backs and wide receivers from years 2012-2014.The combine is a series of tests to evaluate college football players ahead of the NFL Draft. The dataset is available on Canvas. To perform the hypothesis tests below, you will need to upload the data to StatKey and select the appropriate columns. For guidance, refer to the StatKey guide.The dataset contains the following variables:

year Year player participated in combine

position Running Back (RB) or Wide Receiver (WR)

height height in inches

weight weight in pounds

forty yd forty yard dash time in seconds

three cone three cone time in seconds (run between 3 cones in an L shape)

vertical vertical jump height in inches

broad broad jump distance in inches

bench number of bench press repetitions with 225lbs

round round player was drafted (1-7)

Activity 1: Strength and Draft RoundIs there a linear association between a player’s strength, measured using the bench variable,and the round he was drafted in?

1.State the hypotheses of interest.

2.What is the notation and value of the sample statistic?

3.Use StatKey to generate a randomization distribution for these hypotheses. Remember, you will have to upload the dataset to StatKey and select the correct variables.What is the p-value?

4.Complete the p-value interpretation below:If there is ______ linear association between the round he was drafted in and a player’s strength in the population, the chance of seeing a sample correlation of _______ or ___________is _______________.

5.What is the formal conclusion at a significance level of 0.05?

6.What is the conclusion in context?

Answer 1

1.State the hypotheses of interest.

The hypothesis being tested is:

H0: ρ = 0

Ha: ρ ≠ 0

2.What is the notation and value of the sample statistic?

The symbol is t and the statistic is 0.576.

3.Use StatKey to generate a randomization distribution for these hypotheses. Remember, you will have to upload the dataset to StatKey and select the correct variables.What is the p-value?

The p-value is 0.5659.

4.Complete the p-value interpretation below:If there is a linear association between the round he was drafted in and a player’s strength in the population, the chance of seeing a sample correlation of less than or equal to alpha is 0.5659.

5.What is the formal conclusion at a significance level of 0.05?

Since the p-value (0.5659) is greater than the significance level (0.05), we cannot reject the null hypothesis.

6.What is the conclusion in context?

Therefore, we cannot conclude that there is a linear association between a player’s strength, measured using the bench variable,and the round he was drafted in.

	r²	0.003
	r	0.059
	Std. Error	1.885
	n	98
	k	1
	Dep. Var.	round
ANOVA table
Source	SS	df	MS	F	p-value
Regression	1.1791	1	1.1791	0.33	.5659
Residual	340.9944	96	3.5520
Total	342.1735	97
Regression output				confidence interval
variables	coefficients	std. error	t (df=96)	p-value	95% lower	95% upper
Intercept	3.9047
bench	0.0133	0.0231	0.576	.5659	-0.0326	0.0592