In comparison to the previous problem, let us say that the weightlifting supplement company informed you that how long a female weightlifter has been lifting impacts the amount of muscle mass they can gain. Suppose that you changed your data collection method from what you did in Problem 1. Now you randomly select one weightlifter from each group (supplement and placebo) that have been lifting for 39 to 40 months. Next, you randomly sample one weightlifter from each group that have been lifting for 37 to 38 months. Then, you continue this process until the 20th pair of weightlifters have lifted for 2 months or less. The data contains the whole body lean mass difference in pounds and training experience in months. Can you infer that the supplement group gained more muscle mass on average than the placebo group? Use a = 0.05 for any hypothesis test.
In comparison to the previous problem, let us say that the weightlifting supplement company informed you that how long a female weightlifter has been lifting impacts the amount of muscle mass they can gain. Suppose that you changed your data collection method from what you did in Problem 1. Now you randomly select one weightlifter from each group (supplement and placebo) that have been lifting for 39 to 40 months. Next, you randomly sample one weightlifter from each group that have been lifting for 37 to 38 months. Then, you continue this process until the 20th pair of weightlifters have lifted for 2 months or less. The data contains the whole body lean mass difference in pounds and training experience in months. Can you infer that the supplement group gained more muscle mass on average than the placebo group? Use a = 0.05 for any hypothesis test.
Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter7: Distance And Approximation
Section7.3: Least Squares Approximation
Problem 31EQ
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If I could have help with answering Problem two, I would greatly appreciate it. I have the data files in the form of a screenshot. I would have uploaded it as a CSV/Excel file, but I am not able to on this website.
Transcribed Image Text:Row Supplement
1
234
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
2.39
4.03
3.89
2.79
3.12
4.97
2.46
2.61
6.39
5.39
4.94
8.21
3.53
6.07
3.53
8.56
5.21
6.83
5.1
9.39
sExperience
40
38
35
34
32
30
28
26
24
21
20
17
15
14
11
10
8
5
3
2
Placebo
5.22
1.91
1.71
3.63
3.73
2.27
3.95
2.27
4.35
5.08
6.06
8
0.61
-0.39
5.46
3.37
8.48
6.04
5.42
6.14
pExperience
40
37
36
33
31
29
27
25
24
22
19
17
15
13
12
10
7
5
4
1
Transcribed Image Text:Problem 2: Supplement for Weightlifting Continued
In comparison to the previous problem, let us say that the weightlifting supplement company
informed you that how long a female weightlifter has been lifting impacts the amount of muscle
mass they can gain. Suppose that you changed your data collection method from what you did in
Problem 1. Now you randomly select one weightlifter from each group (supplement and
placebo) that have been lifting for 39 to 40 months. Next, you randomly sample one weightlifter
from each group that have been lifting for 37 to 38 months. Then, you continue this process until
the 20th pair of weightlifters have lifted for 2 months or less. The data contains the whole body
lean mass difference in pounds and training experience in months. Can you infer that the
supplement group gained more muscle mass on average than the placebo group? Use α = 0.05
for any hypothesis test.
a) State the research question in one sentence.
b)
Use the question to determine the parameter we are using to conduct statistical inference.
Describe this parameter in one sentence using symbols and a description.
c) State the correct hypotheses for this question.
d) Provide a QQ Plot and a box plot of the differences.
e) Comment on the shape of the distribution and determine if outliers are present.
f) List the conditions necessary to complete this problem.
g) Calculate the test statistic (you may use technology).
h) Construct a Rejection Region graph in StatCrunch.
i)
Calculate the P-value using technology (write the probability statement as well as the
exact probability).
j)
Make a decision whether or not to reject or not reject the null hypothesis using both the
rejection region and the p-value.
k) Draw a conclusion by answering the research question being posed.
1) Comment on the difference in your results from problems 1 and 2. What do you notice?
Problem 3: Confidence Intervals
Construct a 95% confidence interval estimating the difference between means for both problem 1
and problem 2 and interpret each confidence interval. Comparing the two confidence intervals,
what do you notice?
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