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 15 16 17 Weight (9) 777 579 540 647 539 890 672 784 570 628 726 868 1,043 805 833 763 728 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 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.) 9- (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.) P-value= What can you conclude? O Fail to reject H. 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 H. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject H. 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.
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 15 16 17 Weight (9) 777 579 540 647 539 890 672 784 570 628 726 868 1,043 805 833 763 728 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 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.) 9- (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.) P-value= What can you conclude? O Fail to reject H. 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 H. We have convincing evidence that at least one of the predictors length and age are useful for predicting weight. O Reject H. 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.
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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Transcribed Image Text:Stat 3311 Review 3 - Stat 3311, X
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Cengage
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
webassign.net/web/Student/Assignment-Responses/submit?dep=31046654&tags=autosave#question5217328_12
Fish Weight Length Age
Number
(9)
(mm) (years)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
777
579
540
647
539
890
672
784
570
628
726
868
1,043
805
Success Confirmation of Quest x
833
763
728
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
Least Squares Regression Calc X Bb Chapter 13 Simple Linear Regre X
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.)
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 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.
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 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.
Multiple linear Regression Calc X
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