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36. Which of the following is(are) TRUE about the predicted model? * For ou 2 pc

36. Which of the following is(are) TRUE about the predicted model? * For ou 2 pc

MATLAB: An Introduction with Applications
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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2e-16 36. Which of the following is(are) TRUE about the predicted model?* 2 po 1. For every am increase in length, the weight of fish increases by 30.846 grams. II. Weight is linearly dependent on length, at 5% level of significance. OA. I only B. II only C. Both I and II D. Neither I nor II
Transcribed Image Text:2e-16 36. Which of the following is(are) TRUE about the predicted model?* 2 po 1. For every am increase in length, the weight of fish increases by 30.846 grams. II. Weight is linearly dependent on length, at 5% level of significance. OA. I only B. II only C. Both I and II D. Neither I nor II
For number 36: To provide evidence on the classic length-weight-relationship (LWR) model in the fishery literature, a model was created wherein it is of interest to predict the weight (in grams) of a fish based on its length (in cm). R outputs are provided below: Im (formula = Weight Weight Length, data = Dataset10) Residuals: Min 10 Median 30 Max -396.19 -47.96 -6.48 80.11 318.89 Coefficients: Estimate Std. Error t value Pr (>It|) -14.14 <2e-16 *** (Intercept) -584.432 Length 1.164 26.51 <2e-16 *** 0 0.001 0.01 0.05. 0.1* *1 Signif. codes: Residual standard error: 140 on 124 degrees of freedom 0.85, Adjusted R-squared: 0.8488 Multiple R-squared: p-value: < 2.2e-16 F-statistic: 702.8 on i and 124 DF,
Transcribed Image Text:For number 36: To provide evidence on the classic length-weight-relationship (LWR) model in the fishery literature, a model was created wherein it is of interest to predict the weight (in grams) of a fish based on its length (in cm). R outputs are provided below: Im (formula = Weight Weight Length, data = Dataset10) Residuals: Min 10 Median 30 Max -396.19 -47.96 -6.48 80.11 318.89 Coefficients: Estimate Std. Error t value Pr (>It|) -14.14 <2e-16 *** (Intercept) -584.432 Length 1.164 26.51 <2e-16 *** 0 0.001 0.01 0.05. 0.1* *1 Signif. codes: Residual standard error: 140 on 124 degrees of freedom 0.85, Adjusted R-squared: 0.8488 Multiple R-squared: p-value: < 2.2e-16 F-statistic: 702.8 on i and 124 DF,
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