4. What is the value of an estimate of ? a. 3.4369 b. 11.813 c. 543.379 d. 1526.645 5. Suppose we wish to test the hypotheses versus Ha: At least one of the is not 0, using the ANOVA F test. What is the value of the test statistic? a. –11.379 b. –4.230 c. 10.912 d. 129.239

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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4. What is the value of an estimate of ?
a. 3.4369
b. 11.813
c. 543.379
d. 1526.645

5. Suppose we wish to test the hypotheses versus Ha: At least one of the
is not 0, using the ANOVA F test. What is the value of the test statistic?
a. –11.379
b. –4.230
c. 10.912
d. 129.239

Multiple choice questions (50 points)
A correct answer to each question gives 5 points, incorrect answer gives 0 points.
Indicate the answer choice that best completes the statement.
Researchers at a large nutrition and weight-management company are trying to build a model
to predict a person's body fat percent from an array of variables such as body weight, height,
and body measurements around the neck, chest, abdomen, hips, biceps, etc. A variable
selection method is used to build a simple model. SPSS output for the final model is given
below. Based on this, answer questions 1 to 6.
Model Summary
Model
1
Model
1
Model
1
R
9214
Regression
Residual
Total
R Square
.8489
Sum of
Squares
3053.290
543.379
3596.670
(Constant)
Weight
Abdomen circumference
Adjusted
R Square
.842
ANOVA
df
B
-53.954
2
-.162
1.105
46
48
Coefficients
Unstandardized
Coefficients
Std. Error of
the Estimate
3.4369
Mean Square
1526.645
11.813
Std. Error
4.742
038
101
F
129.239
Standardized
Coefficients
Beta
-11.379
-.525
-4.230
1.355 10.912
Sig.
.000
Sig.
.000
.000
.000
Transcribed Image Text:Multiple choice questions (50 points) A correct answer to each question gives 5 points, incorrect answer gives 0 points. Indicate the answer choice that best completes the statement. Researchers at a large nutrition and weight-management company are trying to build a model to predict a person's body fat percent from an array of variables such as body weight, height, and body measurements around the neck, chest, abdomen, hips, biceps, etc. A variable selection method is used to build a simple model. SPSS output for the final model is given below. Based on this, answer questions 1 to 6. Model Summary Model 1 Model 1 Model 1 R 9214 Regression Residual Total R Square .8489 Sum of Squares 3053.290 543.379 3596.670 (Constant) Weight Abdomen circumference Adjusted R Square .842 ANOVA df B -53.954 2 -.162 1.105 46 48 Coefficients Unstandardized Coefficients Std. Error of the Estimate 3.4369 Mean Square 1526.645 11.813 Std. Error 4.742 038 101 F 129.239 Standardized Coefficients Beta -11.379 -.525 -4.230 1.355 10.912 Sig. .000 Sig. .000 .000 .000
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