The article The Undrained Strength of Some Thawed Permafrost Sols contained the accompanying data on the flowing -shear strength of sandy (P) -depth (m) watero (5) The predicted values and residuals were computed using the estimated regression equation Y 14.7 8.8 31.6 48.0 36.7 26.9 25.6 36.7 25.8 10.0 6.0 39.0 Predicted Residual 16.0 7.0 39.1 16.8 6.8 38.4 20.7 7.2 33.8 23.24 38.8 8.5 33.7 16.9 6.6 27.8 27.0 8.1 33.2 SSResid- SSRe 26.99 14.88 The value The value The value The value 15.50 15.45 4.6 26.4 24.9 9.8 37.9 7.3 10 347 128 21 36.5 (4) Use the given information to calculate SSResid, SST, and SSReg (Round your answers to four decimal places) -0.98 7.68 1.40 2.36 0.55 (b) Calculate for this regression model (Round your answer to three decimal places) -O How would you interpret this value? gives the percentage of water content values in the sample that are equal to the values predicted by the model gives the percentage of observed variation in shear strength of sandy soll that can be explained by the fitted model gives the percentage of shear strength of sandy soll values in the sample that are equal to the values predicted by the model gives the percentage of observed variation in water content that can be explained by the fed model (4) Use the value of Calculate the test statistic. (Round your answer to two decimal places) from part and a 0.05 level of significance to carry out a model utility Fest Use technology to calculate the value. (Round your answer to four decimal places) What can you conclude Fall to reject. We do not have convincing evidence that the multiple regression model is usu Reject We do not have convincing evidence that the multiple regression model is us Reject We have convincing evidence that the multiple regression model is useful Flowe have convincing evidence that the multiple regression model is useful
The article The Undrained Strength of Some Thawed Permafrost Sols contained the accompanying data on the flowing -shear strength of sandy (P) -depth (m) watero (5) The predicted values and residuals were computed using the estimated regression equation Y 14.7 8.8 31.6 48.0 36.7 26.9 25.6 36.7 25.8 10.0 6.0 39.0 Predicted Residual 16.0 7.0 39.1 16.8 6.8 38.4 20.7 7.2 33.8 23.24 38.8 8.5 33.7 16.9 6.6 27.8 27.0 8.1 33.2 SSResid- SSRe 26.99 14.88 The value The value The value The value 15.50 15.45 4.6 26.4 24.9 9.8 37.9 7.3 10 347 128 21 36.5 (4) Use the given information to calculate SSResid, SST, and SSReg (Round your answers to four decimal places) -0.98 7.68 1.40 2.36 0.55 (b) Calculate for this regression model (Round your answer to three decimal places) -O How would you interpret this value? gives the percentage of water content values in the sample that are equal to the values predicted by the model gives the percentage of observed variation in shear strength of sandy soll that can be explained by the fitted model gives the percentage of shear strength of sandy soll values in the sample that are equal to the values predicted by the model gives the percentage of observed variation in water content that can be explained by the fed model (4) Use the value of Calculate the test statistic. (Round your answer to two decimal places) from part and a 0.05 level of significance to carry out a model utility Fest Use technology to calculate the value. (Round your answer to four decimal places) What can you conclude Fall to reject. We do not have convincing evidence that the multiple regression model is usu Reject We do not have convincing evidence that the multiple regression model is us Reject We have convincing evidence that the multiple regression model is useful Flowe have convincing evidence that the multiple regression model is useful
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Transcribed Image Text:Stat 3311 Review 3 - Stat 3311, X
← → C D
Cengage
The article The Undrained Strength of Some Thawed Permafrost Soils" contained the accompanying data on the following
y-shear strength of sandy soil (kPa)
x-depth (m)
*-water content (56)
2
₂²X₁-X₂², and X₂-X₁X₂
The predicted values and residuals were computed using the estimated regression equation
9--149.41-15.76x, + 13.28x₂ +0.091x,-0.249x+0.481x
where x₂-x₂².
x₁
%₂
14.7 8.8
8.8 31.6
48.0 36.7 26.9
25.6 36.7 25.8
10.0 6.0 39.0
16.0 7.0 39.1
16.8 6.8 38.4
20.7 7.2 33.8
38.8 8.5 33.7
16.9
6.6 27.8
27.0 8.1 33.2
16.0 4.6 26.4
24,9
37.9
3.0 34.7
12.8 2.1 36.5
7.3
9.8
SSTO-
SSResid-
SSRegr
webassign.net/web/Student/Assignment-Responses/submit?dep=31046654&tags=autosave#question5217312_6
Predicted y Residual
23.67
46.58
26.99
10.98
14.88
15.95
23.24
25.69
15.50
24.64
15.45
29.12
15.14
7.68
-8.97
1.42
-1.39
-0.98
1.12
0.85
-2.54
13.11
1.40
2.36
0.55
Success Confirmation of Quest x
-4.22
-7.84
5.12
(a) Use the given information to calculate SSResid, SSTO, and SSRegr. (Round your answers to four decimal places.)
(b) Calculate R² for this regression model. (Round your answer to three decimal places.)
R²
How would you interpret this value?
The value R² gives the percentage of water content values in the sample that are equal to the values predicted by the model.
The value gives the percentage of observed variation in shear strength of sandy soil that can be explained by the fitted model.
The value R² gives the percentage of shear strength of sandy soil values in the sample that are equal to the values predicted
O The value R² gives the percentage of observed variation in water content that can be explained by the fitted model.
(c) Use the value of R2 from part (b) and a 0.05 level of significance to carry out a model utility Ftest.
Calculate the test statistic. (Round your answer to two decimal places.)
F=
Use technology to calculate the P-value. (Round your answer to four decimal places.)
P-value-
What can you conclude?
O Fail to reject H. We do not have convincing evidence that the multiple regression model is useful.
O Reject H. We do not have convincing evidence that the multiple regression model is useful.
O Reject H. We have convincing evidence that the multiple regression model is useful.
O Fail to reject H. We have convincing evidence that the multiple regression model is useful.
D
Least Squares Regression Calc X Bb Chapter 13 Simple Linear Regre X
the model.
Multiple linear Regression Calc X
+
Q
☆
9
⠀
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