Directions: Click on the Data button below to display the data. Copy the data into a statistical software package and click the Data button a second time to hide it. Then perform an analysis of variance (ANOVA to determine whether or not the differences in weight gain between the treatment groups is statistically significant. Data Control CBT Family 1.1 0.5 12.1 -1.2 -7.3 11.4 0.4 -3.5 3.5 -1.4 14.3 10.8 -4.4 -1.2 12.9 12.9 -11.7 -4.2 3.8 -13.7 0.9 17.4 10.2 8.9 -7.3 -6.2 23 2.4 6.3 -4.3 13.1 1.4 -2.9 7.9 -7.4 12.9 0.4 7.7 14.5 -5.2 2.4 7.6 20.7 11.1 3.8 -8 1 6.6 1 -1.9 10.7 -3.2 -10 2.3 -4.3 0.7 -7.5 -2 1.8 0.9 -0.6 1.2 2.6 10.7 5.2 2.1 16.7 5.1 -11.3 -0.3 16.5 -0.9

MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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4)nterpret the results of the significance test. Is this result statistically significant? Is this result important from a practical perspective?

Directions: Click on the Data button below to display the data. Copy the data into a statistical software
package and click the Data button a second time to hide it. Then perform an analysis of variance (ANOVA)
to determine whether or not the differences in weight gain between the treatment groups is statistically
significant.
Data
Control
CBT
Family
1.1
0.5
12.1
-1.2
-7.3
11.4
0.4
-3.5
3.5
-1.4
14.3
10.8
-4.4
-1.2
12.9
12.9
-11.7
-4.2
3.8
-13.7
0.9
17.4
10.2
8.9
-7.3
-6.2
23
2.4
6.3
-4.3
13.1
1.4
-2.9
7.9
-7.4
12.9
0.4
7.7
14.5
-5.2
2.4
7.6
20.7
11.1
3.8
-8
6.6
1
-1.9
10.7
-3.2
-10
2.3
-4.3
0.7
-7.5
-2
1.8
0.9
-0.6
1.2
2.6
10.7
5.2
2.1
16.7
5.1
-11.3
-0.3
16.5
-0.9
Transcribed Image Text:Directions: Click on the Data button below to display the data. Copy the data into a statistical software package and click the Data button a second time to hide it. Then perform an analysis of variance (ANOVA) to determine whether or not the differences in weight gain between the treatment groups is statistically significant. Data Control CBT Family 1.1 0.5 12.1 -1.2 -7.3 11.4 0.4 -3.5 3.5 -1.4 14.3 10.8 -4.4 -1.2 12.9 12.9 -11.7 -4.2 3.8 -13.7 0.9 17.4 10.2 8.9 -7.3 -6.2 23 2.4 6.3 -4.3 13.1 1.4 -2.9 7.9 -7.4 12.9 0.4 7.7 14.5 -5.2 2.4 7.6 20.7 11.1 3.8 -8 6.6 1 -1.9 10.7 -3.2 -10 2.3 -4.3 0.7 -7.5 -2 1.8 0.9 -0.6 1.2 2.6 10.7 5.2 2.1 16.7 5.1 -11.3 -0.3 16.5 -0.9
1. State the null and alternative hypotheses.
2. Compute the test statistic. Document how SSTR and SSE were computed. Use 4 decimal places for
the sample means, sample standard deviations and the grand mean and round your answers for SSTR
and SSE to 2 decimal places.
Edit -
Insert
Formats
I
X,
A
<>
E- E E
Σ Σ
Use the values for SSTR and SSE to complete the following ANOVA table. Round each of your answers
to 2 decimal places.
Source
S.S.
df
M.S.
F
Treatment
Error
Total
3. Compute the p-value. Provide the name of the distribution and the parameters used to compute the
p-value. Then enter your answer rounded to 4 decimal places.
p-value =
Transcribed Image Text:1. State the null and alternative hypotheses. 2. Compute the test statistic. Document how SSTR and SSE were computed. Use 4 decimal places for the sample means, sample standard deviations and the grand mean and round your answers for SSTR and SSE to 2 decimal places. Edit - Insert Formats I X, A <> E- E E Σ Σ Use the values for SSTR and SSE to complete the following ANOVA table. Round each of your answers to 2 decimal places. Source S.S. df M.S. F Treatment Error Total 3. Compute the p-value. Provide the name of the distribution and the parameters used to compute the p-value. Then enter your answer rounded to 4 decimal places. p-value =
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