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This exercise requires the use of a statistical software package. An article included the accompanying data on 17 fish caught in 2 consecutive years. Year Year 1 Year 2 Fish Number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Weight Length (9) 775 579 540 649 539 892 674 782 570 628 726 868 1,041 805 831 763 726 Age (mm) (years) 410 368 357 373 361 385 380 400 407 410 421 446 478 441 454 440 427 9 11 15 12 9 9 10 12 12 13 12 19 19 18 12 12 12 (a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x₁ for length and x₂ for age. Round your numerical values to two decimal places.) ŷ = (b) Carry out the model utility test to determine whether at least one of the predictors length and age are useful for predicting weight. Use a significance level of 0.05. 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 Reject Ho. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight.

This exercise requires the use of a statistical software package. An article included the accompanying data on 17 fish caught in 2 consecutive years. Year Year 1 Year 2 Fish Number 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Weight Length (9) 775 579 540 649 539 892 674 782 570 628 726 868 1,041 805 831 763 726 Age (mm) (years) 410 368 357 373 361 385 380 400 407 410 421 446 478 441 454 440 427 9 11 15 12 9 9 10 12 12 13 12 19 19 18 12 12 12 (a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x₁ for length and x₂ for age. Round your numerical values to two decimal places.) ŷ = (b) Carry out the model utility test to determine whether at least one of the predictors length and age are useful for predicting weight. Use a significance level of 0.05. 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 Reject Ho. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight.

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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This exercise requires the use of a statistical software package. An article included the accompanying data on 17 fish caught in 2 consecutive years. Year Year 1 Year 2 Fish Number 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17 Weight Length (g) 775 579 540 649 539 892 674 782 570 726 868 1,041 805 831 763 726 Age (mm) (years) 410 368 357 373 361 385 380 400 407 410 421 446 478 441 454 440 427 9 11 15 12 9 9 10 12 12 13 12 19 19 18 12 12 12 (a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x₁ for length and x₂ for age. Round your numerical values to two decimal places.) ŷ = (b) Carry out the model utility test to determine whether at least one of the predictors length and age are useful for predicting weight. Use a significance level of 0.05. 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 Reject H. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight.
Transcribed Image Text:This exercise requires the use of a statistical software package. An article included the accompanying data on 17 fish caught in 2 consecutive years. Year Year 1 Year 2 Fish Number 1 2 3 4 5 6 7 8 9 11 12 13 14 15 16 17 Weight Length (g) 775 579 540 649 539 892 674 782 570 726 868 1,041 805 831 763 726 Age (mm) (years) 410 368 357 373 361 385 380 400 407 410 421 446 478 441 454 440 427 9 11 15 12 9 9 10 12 12 13 12 19 19 18 12 12 12 (a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x₁ for length and x₂ for age. Round your numerical values to two decimal places.) ŷ = (b) Carry out the model utility test to determine whether at least one of the predictors length and age are useful for predicting weight. Use a significance level of 0.05. 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 Reject H. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Fail to reject Ho. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight.
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