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 ŷ Year 1 Year 2 Fish Number 1 2 P-value= 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Weight (9) 777 581 538 649 537 892 672 782 570 628 726 868 1,043 805 833 765 728 Length 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 (a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x, for length and x₂ for age. Round your numerical values to two decimal places.) 12 (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.) Use technology to calculate the P-value. (Round your answer to four decimal places.) What can you conclude? O Fail to reject H. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject H. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight. OD
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 ŷ Year 1 Year 2 Fish Number 1 2 P-value= 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 Weight (9) 777 581 538 649 537 892 672 782 570 628 726 868 1,043 805 833 765 728 Length 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 (a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x, for length and x₂ for age. Round your numerical values to two decimal places.) 12 (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.) Use technology to calculate the P-value. (Round your answer to four decimal places.) What can you conclude? O Fail to reject H. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject H. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight. OD
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: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
ŷ
Year 1
Year 2
Fish
Number
1
2
P-value=
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
Weight
(9)
777
581
538
649
537
892
672
782
570
628
726
868
1,043
805
833
765
728
Length 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
(a) Fit a multiple regression model to describe the relationship between weight and the predictors length and age. (Use x, for length and x₂ for age. Round your numerical values to two decimal places.)
12
(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.)
Use technology to calculate the P-value. (Round your answer to four decimal places.)
What can you conclude?
O Fail to reject H. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight.
O Reject H. We do not have convincing evidence that at least one of the predictors length and age are useful for predicting weight.
OD
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