38. Which of the following is(are) TRUE about the predicted model?* I. At 5% level of significance, there is sufficient evidence to say that weight is linearly dependent on at least one of the predictors in the model. II. The variation in the weight that is explained by length, width, and species type is 93.13% while the remaining percent is explained by other factors not considered in the model. O A. I only B. II only C. Both I and II OD. Neither I nor II

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38. Which of the following is(are) TRUE about the predicted model? *
1. At 5% level of significance, there is sufficient evidence to say that weight is
linearly dependent on at least one of the predictors in the model.
II. The variation in the weight that is explained by length, width, and species
type is 93.13% while the remaining percent is explained by other factors not
considered in the model.
A. I only
B. II only
C. Both I and II
D. Neither I nor II
priate conclusion if we test the regression
Transcribed Image Text:38. Which of the following is(are) TRUE about the predicted model? * 1. At 5% level of significance, there is sufficient evidence to say that weight is linearly dependent on at least one of the predictors in the model. II. The variation in the weight that is explained by length, width, and species type is 93.13% while the remaining percent is explained by other factors not considered in the model. A. I only B. II only C. Both I and II D. Neither I nor II priate conclusion if we test the regression
humbers 37 to 41: Another model was created wherein three explanatory
variables were included to predict weight, specifically: length (in cm), width (in
cm), and species type (1, 2, 3, or 4). R outputs are provided below:
Call:
im (formula = Weight-Length + Species 2 + Species 3+ Species 4+
Width, data Dataset)
Residuals:
Min
10 Median
30
-187.89 -62.41 -18.11
Max
35.62 392.46
Coefficients:
Estimate Std. Error t value Pr(>iti)
115.443 -9.096 2.43e-15 ***
(Intercept) -1050.047
Length
37.149
1.202 30.895 <2e-16 ***
20.172
32.896 0.613 0.5409
Species 2
Species_3 -225.525
53.757
48.363 -4.663 8.15e-06 ***
29.854 1.801 0.0743
0.0456 *
Species_4
Width
17.676
8.749 2.020
0 ***** 0.001 **** 0.01 *** 0.05 .' 0.1'' 1
Signif. codes:
Residual standard error: 96.37 on 120 degrees of freedom
Multiple R-squared: 0.9313, Adjusted R-squared: 0.9284
F-statistic: 325.1 on 5 and 120 DF, p-value: <2.2e-16
Tropression
Transcribed Image Text:humbers 37 to 41: Another model was created wherein three explanatory variables were included to predict weight, specifically: length (in cm), width (in cm), and species type (1, 2, 3, or 4). R outputs are provided below: Call: im (formula = Weight-Length + Species 2 + Species 3+ Species 4+ Width, data Dataset) Residuals: Min 10 Median 30 -187.89 -62.41 -18.11 Max 35.62 392.46 Coefficients: Estimate Std. Error t value Pr(>iti) 115.443 -9.096 2.43e-15 *** (Intercept) -1050.047 Length 37.149 1.202 30.895 <2e-16 *** 20.172 32.896 0.613 0.5409 Species 2 Species_3 -225.525 53.757 48.363 -4.663 8.15e-06 *** 29.854 1.801 0.0743 0.0456 * Species_4 Width 17.676 8.749 2.020 0 ***** 0.001 **** 0.01 *** 0.05 .' 0.1'' 1 Signif. codes: Residual standard error: 96.37 on 120 degrees of freedom Multiple R-squared: 0.9313, Adjusted R-squared: 0.9284 F-statistic: 325.1 on 5 and 120 DF, p-value: <2.2e-16 Tropression
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