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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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A statistical program is recommended.
The authors of an article found that the speed of a prey (twips/s) and the length of a prey (twips ✕ 100) are good predictors of the time (seconds) required to catch the prey. (A twip is a measure of distance used by programmers.) Data were collected in an experiment in which subjects were asked to "catch" an animal of prey moving across his or her computer screen by clicking on it with the mouse. The investigators varied the length of the prey and the speed with which the prey moved across the screen.
The following data are consistent with summary values and a graph given in the article. Each value represents the average catch time over all subjects. The order of the various speed-length combinations was randomized for each subject.
Prey Length
Prey Speed
Catch Time
7
20
1.10
6.
20
1.21
5
20
1.23
4
20
1.41
3
20
1.49
3
40
1.41
4
40
1.36
6
40
1.29
7
40
1.27
7
80
1.40
6.
60
1.38
80
1.40
7
100
1.43
6
100
1.43
7
120
1.70
5
80
1.50
3
80
1.41
6
100
1.49
3
120
1.89
(a) Fit a multiple regression model for predicting catch time using prey length and speed as predictors. (Use x, for prey length and x, for speed. Round your answers to three decimal places.)
x2
(b) Predict the catch time for an animal of prey whose length is 6 and whose speed is 50. (Round your answer to three decimal places.)
(c) Is the multiple regression model useful for predicting catch time? Test the relevant hypotheses using a = 0.05.
State the null and alternative hypotheses.
O Ho: B1 = B2 = 0
H: neither B, nor B2 is 0.
O Ho: B, = B2 = o
H: at least one of B, or B, is not 0.
O Ho: neither B, nor B, is 0.
H: B1 = B2 = 0
%3D
O H: at least one of B, or B, is not 0.
H: B, = B2 = 0
%3D
Transcribed Image Text:Prey Length Prey Speed Catch Time 7 20 1.10 6. 20 1.21 5 20 1.23 4 20 1.41 3 20 1.49 3 40 1.41 4 40 1.36 6 40 1.29 7 40 1.27 7 80 1.40 6. 60 1.38 80 1.40 7 100 1.43 6 100 1.43 7 120 1.70 5 80 1.50 3 80 1.41 6 100 1.49 3 120 1.89 (a) Fit a multiple regression model for predicting catch time using prey length and speed as predictors. (Use x, for prey length and x, for speed. Round your answers to three decimal places.) x2 (b) Predict the catch time for an animal of prey whose length is 6 and whose speed is 50. (Round your answer to three decimal places.) (c) Is the multiple regression model useful for predicting catch time? Test the relevant hypotheses using a = 0.05. State the null and alternative hypotheses. O Ho: B1 = B2 = 0 H: neither B, nor B2 is 0. O Ho: B, = B2 = o H: at least one of B, or B, is not 0. O Ho: neither B, nor B, is 0. H: B1 = B2 = 0 %3D O H: at least one of B, or B, is not 0. H: B, = B2 = 0 %3D
Calculate the test statistic. (Round your answer to two decimal places.)
What can be said about the P-value for this test?
O P-value > 0.100
O 0.050 < P-value < 0.100
O 0.010 < P-value < 0.050
O 0.001 < P-value < 0.010
O P-value < 0.001
What can you conclude?
O Fail to reject H.. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that 8, and 8, are both not 0.
O Reject Hn. We have convincing evidence that the multiple regression model is useful and can conclude that neither B, nor 8, is 0.
O Reject H.. We have convincing evidence that the multiple regression model is useful and can conclude that at least one of B, or 8, is not 0.
O Fail to reject H.. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that at least one of B, or B, is not 0.
(d) The authors of the article suggest that a simple linear regression model with the single predictor
length
speed
might be a better model for predicting catch time. Calculate these x values and use them to fit a simple linear regression model. (Round your answers to three decimal places.)
(e)
the
considered (the multiple regression
part (a)
the simple linear regression
part (d)) would you recommen
predicting catch time? Justify your choice.
O Since the 2 value is greater for the first model than for the second, but the adjusted r2 value is greater for the second model than for the first, the second model is preferable to the second. The second model is the one that accounts for the greater proportion of the observed variation in catch time.
O Since the r value is greater for the second model than for the first, but the adjusted r2 value is greater for the first model than for the second, the first model is preferable to the second. The first model is the one that accounts for the greater proportion of the observed variation in catch time.
O Since both the r2 and the adjusted r2 values are greater for the first model than for the second, the first model is preferable to the second. The first model is the one that accounts for the greater proportion of the observed variation in catch time.
O Since both the r2 and the adjusted r2 values are greater for the second model than for the first, the second model is preferable to the first. The second model is the one that accounts for the greater proportion of the observed variation in catch time.
Transcribed Image Text:Calculate the test statistic. (Round your answer to two decimal places.) What can be said about the P-value for this test? O P-value > 0.100 O 0.050 < P-value < 0.100 O 0.010 < P-value < 0.050 O 0.001 < P-value < 0.010 O P-value < 0.001 What can you conclude? O Fail to reject H.. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that 8, and 8, are both not 0. O Reject Hn. We have convincing evidence that the multiple regression model is useful and can conclude that neither B, nor 8, is 0. O Reject H.. We have convincing evidence that the multiple regression model is useful and can conclude that at least one of B, or 8, is not 0. O Fail to reject H.. We do not have convincing evidence that the multiple regression model is useful and cannot conclude that at least one of B, or B, is not 0. (d) The authors of the article suggest that a simple linear regression model with the single predictor length speed might be a better model for predicting catch time. Calculate these x values and use them to fit a simple linear regression model. (Round your answers to three decimal places.) (e) the considered (the multiple regression part (a) the simple linear regression part (d)) would you recommen predicting catch time? Justify your choice. O Since the 2 value is greater for the first model than for the second, but the adjusted r2 value is greater for the second model than for the first, the second model is preferable to the second. The second model is the one that accounts for the greater proportion of the observed variation in catch time. O Since the r value is greater for the second model than for the first, but the adjusted r2 value is greater for the first model than for the second, the first model is preferable to the second. The first model is the one that accounts for the greater proportion of the observed variation in catch time. O Since both the r2 and the adjusted r2 values are greater for the first model than for the second, the first model is preferable to the second. The first model is the one that accounts for the greater proportion of the observed variation in catch time. O Since both the r2 and the adjusted r2 values are greater for the second model than for the first, the second model is preferable to the first. The second model is the one that accounts for the greater proportion of the observed variation in catch time.
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