HW 11 (PSY3211)
Homework 11 (PSY3211)
Instructions: Do you recall the assignment we did a few weeks ago when we calculated the standard deviation and variance for the number of sacks for the different football teams in the AFC and NFC conferences of the National Football League? Well, let’s revisit those data to figure out if there is a significant difference between the two conferences. Our goal is to test if the number of sacks are different for the two groups of teams (for the 16 teams in the AFC versus the 16 teams in the NFC) (note this is the same as the data from your Assignment #6---you might want to look back at that assignment to see your means, SDs, and Variance calculations to save yourself some time on this assignment!).
To refresh your memory from assignment 6: In Football, when the quarterback is tackled before they can throw the ball, it’s called getting “sacked.” Getting sacked is a bad thing because it means that they lose yards (they are farther away from the goal) and they lose a chance to advance the ball.
The National Football League (NFL) is divided into two different conferences (groups of teams), the NFC and the AFC. Below are the number of times the quarterbacks were sacked during the regular 2021 season for every football team in the AFC and NFC.
|
AFC |
|
|
AFC Team Name |
Number of times sacked |
|
Ravens |
57 |
|
Bangles |
55 |
|
Steelers |
38 |
|
Browns |
49 |
|
Bills |
27 |
|
Dolphins |
40 |
|
Patriots |
28 |
|
Jets |
53 |
|
Texans |
44 |
|
Colts |
32 |
|
Jaguars |
32 |
|
Titans |
47 |
|
Broncos |
40 |
|
Kansas City |
28 |
|
Raiders |
40 |
|
Chargers |
31 |
|
NFC |
|
|
NFC Team Name |
Number of times sacked |
|
Bears |
58 |
|
Lions |
36 |
|
Packers |
33 |
|
Vikings |
30 |
|
Cowboys |
33 |
|
Giants |
38 |
|
Eagles |
31 |
|
Washington |
43 |
|
Falcons |
40 |
|
Panthers |
52 |
|
Saints |
37 |
|
Buccaneers |
23 |
|
Cardinals |
39 |
|
Rams |
31 |
|
49ers |
33 |
|
Seahawks |
46 |
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What is the null hypothesis?
Question 20.5 pts
What is the alternative hypothesis?
What is the risk level?
Group of answer choices
· .25
· .5
· .01
· .05
Question 40.25 pts
What is the best statistical test to use?
Group of answer choices
· z-test
· correlation test
· t-Test for independent samples
· ANOVA
· t-Test for dependent samples
Compute the test statistic. The formula is below for you. Also, remember to use the variance rather than the standard deviation in your calculation. You have already calculated the variance for your previous assignment, so that part is already done! Put your calculated t value below, round your answer to two decimal places:
t=(m1−m2)(((n1−1)s12+(n2−1)s22)n1+n2−2)((n1+n2)n1n2)
Now it's time to compare our obtained value (the one you just calculated) to the critical value. First, we'll need the degrees of freedom. What are the degrees of freedom?
Group of answer choices
· 40
· 19
· 28
· 30
Should we use a "one tailed" or a "two tailed" test for this?
Hint: To figure this out, think about whether it is directional or non-directional. Take a look at your alternative hypothesis (above!), and think about the prompt for the assignment---did we expect there to be more sacks in one group than the other or were simply testing whether they were different?
Group of answer choices
· one tailed
· two tailed
Question 81 pts
What is the critical value for this statistical test? (hint: you'll need your answers to the previous two questions, as well as your "level of risk"; remember, if the exact degrees of freedom aren't in the t-test table of critical values, you can choose the closest value that is there).
Group of answer choices
· 2.043
· 2.049
· 1.701
· 1.562
Write up your results as you would see it in a results section of an empirical research paper (in APA style). Make sure to include the means and SDs.
Based on your answer to the previous question, what is your decision?
Group of answer choices
· Fail to reject the null hypothesis
· Reject the null hypothesis
· Not enough information to decide
Question 111 pts
Imagine that you also wanted to compare if there was a difference in the number of touch towns scored between the NFC and AFC. You write up the following results:
An independent samples t-Test comparing the average number of touchdowns scored during the regular season between the NFC and AFC was statistically significant, t(30) = 1.92, p < .05. The number of touchdowns scored by the teams in the AFC (M = 25.125, SD = 7.54) than the NFC (M = 22.25, SD = 2.54.
Calculate the effect size for this new t-test, using the Pooled Variance Formula (Below). Round your answer to two decimal places.
ES=(m1−m2)(σ12+σ22)2
What "size" is this effect size?
Group of answer choices
· There isn't enough information to answer this question.
· Large
· Medium
· Small
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