A statistical program is recommended. An article gave the data, shown in the table below, on dimensions of 27 representative food products. Product Material Height 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 glass glass glass glass plastic glass glass plastic plastic plastic tin plastic glass glass glass glass cardboard cardboard glass glass glass glass glass glass plastic tin tin 7.7 6.2 8.5 10.4 OH₂A₁B₂B₂=0 8.0 8.7 10.2 10.5 3.4 6.9 10.9 9.7 10.1 13.0 13.0 11.0 8.7 17.1 16.5 16.5 9.7 17.8 14.0 13.6 27.9 19.5 13.8 Maximum Width 2.50 2.90 OH: at least one of ₁, ₂ or B, is not 0 H₂: A₁-A₂ =B₂ = 0 2.15 OH: A₂ and , are all not 0 H₂: A₁-A₂=₂=0 2.90 3.20 2.00 1.60 4.80 5.90 5.80 2.90 2.45 2.60 2.60 2.70 3.10 5.10 10.20 3.50 2.70 3.00 2.70 2.50 2.40 4.40 7.50 4.25 Minimum Width (c) Carry out a model utility Ftest at a 0.05 significance level. State the null and alternative hypotheses. B₂ =B₂ = 0 OH₂ B₁ H: ₂ and , are all not 0 H: at least one of ₁.₂ or ₂ is not 0 1.80 2.70 2.00 2.60 3.15 1.80 1.50 3.80 5.00 4.75 2.80 2.10 2.20 2.60 2.60 2.90 5.10 10.20 3.50 1.20 1.70 1.75 1.70 1.20 1.20 7.50 4.25 Elongation Volume 1.50 1.07 1.98 1.79 1.25 2.17 3.19 1.09 0.29 0.59 1.88 1.98 1.94 2.50 2.41 1.77 0.85 0.84 2.36 3.06 1.62 3.30 2.80 2.83 (b) Why should we consider adjusted R² instead of R² when evaluating this model? O We should consider the adjusted O We should consider the adjusted O We should consider the adjusted O We should consider the adjusted instead of instead of instead of instead of 3.17 1.30 1.62 130 139 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= 180 281 332 93 119 515 325 568 339 180 235 239 363 312 631 1248 651 306 320 (a) Fit a multiple regression model for predicting the volume (in ml) of a package based on its minimum width, maximum width, and elongation score. (Round your numerical values to two decimal places. Use x, for minimum width, x, for the maximum width and x, for the elongation score.) ŷ = 310 247 204 1204 2329 731 because it takes into account the number of predictors used in the model. In this case the adjusted is noticeably less than ². because it does not take into account the number of predictors used in the model. In this case the adjusted is noticeably greater than ². because it takes into account the number of predictors used in the model. In this case the adjusted is noticeably greater than ². because it does not take into account the number of predictors used in the model. In this case the adjusted is noticeably less than ². What can you conclude? O Reject H. We have convincing evidence that the multiple regression model is useful and can conclude that at least one of ₁.₂ or ₂ 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 ₁, ₂ and S, are all 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 ₁, ₂ or ₂ is not 0. O Reject H. We have convincing evidence that the multiple regression model is useful and can conclude that ₁₂ and , are all not 0.

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.
An article gave the data, shown in the table below, on dimensions of 27 representative food products.
Product
1
2
3
4
6
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
Material Height
glass
glass
glass
glass
plastic
glass
glass
plastic
plastic
plastic
tin
glass
glass
glass
glass
glass
plastic
tin
7.7
6.2
8.5
10.4
8.0
8.7
O H₁₂ : B₁ =B₂ =B₂ = 0
10.2
plastic
glass
glass
glass
glass
cardboard 8.7
cardboard 17.1
glass
10.5
3.4
6.9
10.9
9.7
10.1
13.0
13.0
11.0
16.5
16.5
9.7
17.8
14.0
13.6
27.9
19.5
13.8
Maximum
Width
HB₁ B₂ and ₂ are all not 0
2.50
2.90
OH: at least one of B₁, B₂ or 3 is not 0
H₁₂ : B₁ =B₂ =B₂ = 0
2.15
2.90
3.20
2.00
1.60
4.80
5.90
5.80
2.90
2.45
2.60
2.60
2.70
3.10
5.10
10.20
3.50
2.70
3.00
2.70
2.50
2.40
4.40
7.50
4.25
Minimum
Width
(c) Carry out a model utility F test at a 0.05 significance level.
State the null and alternative hypotheses.
OH₁: B₁ =B₂ =B₂ = 0
1.80
H₂: at least one of B₁ B₂ or B₂ is not 0
2.70
2.00
2.60
3.15
1.80
1.50
3.80
5.00
4.75
2.80
2.10
2.20
2.60
2.60
2.90
5.10
10.20
3.50
1.20
1.70
1.75
1.70
1.20
1.20
7.50
4.25
Elongation Volume
1.50
1.07
1.98
OHB₁ B₂ and B, are all not 0
H₂1 P₁ =B₂ =B₂ = 0
Calculate the test statistic. (Round your answer to two decimal places.)
F=
1.79
1.25
2.17
3.19
1.09
0.29
0.59
1.88
1.98
1.94
2.50
2.41
1.77
0.85
0.84
2.36
3.06
1.62
3.30
2.80
(b) Why should we consider adjusted R² instead of R² when evaluating this model?
O We should consider the adjusted ² instead of
O We should consider the adjusted instead of
O We should consider the adjusted ² instead of
O We should consider the adjusted instead of
2.83
3.17
1.30
1.62
130
139
Use technology to calculate the P-value. (Round your answer to four decimal places.)
P-value =
180
281
332
93
515
325
568
339
180
235
239
363
312
631
1248
651
306
(a) Fit a multiple regression model for predicting the volume (in ml) of a package based on its minimum width, maximum width, and elongation score. (Round your numerical values to two decimal places. Use x for minimum width, x₂ for the maximum width and x, for the elongation score.)
ŷ =
320
310
247
204
1204
2329
because it takes into account the number of predictors used in the model. In this case the adjusted is noticeably less than ².
because it does not take into account the number of predictors used in the model. In this case the adjusted ² is noticeably greater than 2.
because it takes into account the number of predictors used in the model. In this case the adjusted 2 is noticeably greater than r².
because it does not take into account the number of predictors used in the model. In this case the adjusted ² is noticeably less than ².
731
What can you conclude?
O Reject H. We have convincing evidence that the multiple regression model is useful and can conclude that at least one of B₁, B₂ or 3 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 B₁, B₂ and ₂ are all 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 B₁, B₂ or 3 is not 0.
O Reject H. We have convincing evidence that the multiple regression model is useful and can conclude that ₁, ₂ and ₂ are all not 0.
Transcribed Image Text:A statistical program is recommended. An article gave the data, shown in the table below, on dimensions of 27 representative food products. Product 1 2 3 4 6 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 Material Height glass glass glass glass plastic glass glass plastic plastic plastic tin glass glass glass glass glass plastic tin 7.7 6.2 8.5 10.4 8.0 8.7 O H₁₂ : B₁ =B₂ =B₂ = 0 10.2 plastic glass glass glass glass cardboard 8.7 cardboard 17.1 glass 10.5 3.4 6.9 10.9 9.7 10.1 13.0 13.0 11.0 16.5 16.5 9.7 17.8 14.0 13.6 27.9 19.5 13.8 Maximum Width HB₁ B₂ and ₂ are all not 0 2.50 2.90 OH: at least one of B₁, B₂ or 3 is not 0 H₁₂ : B₁ =B₂ =B₂ = 0 2.15 2.90 3.20 2.00 1.60 4.80 5.90 5.80 2.90 2.45 2.60 2.60 2.70 3.10 5.10 10.20 3.50 2.70 3.00 2.70 2.50 2.40 4.40 7.50 4.25 Minimum Width (c) Carry out a model utility F test at a 0.05 significance level. State the null and alternative hypotheses. OH₁: B₁ =B₂ =B₂ = 0 1.80 H₂: at least one of B₁ B₂ or B₂ is not 0 2.70 2.00 2.60 3.15 1.80 1.50 3.80 5.00 4.75 2.80 2.10 2.20 2.60 2.60 2.90 5.10 10.20 3.50 1.20 1.70 1.75 1.70 1.20 1.20 7.50 4.25 Elongation Volume 1.50 1.07 1.98 OHB₁ B₂ and B, are all not 0 H₂1 P₁ =B₂ =B₂ = 0 Calculate the test statistic. (Round your answer to two decimal places.) F= 1.79 1.25 2.17 3.19 1.09 0.29 0.59 1.88 1.98 1.94 2.50 2.41 1.77 0.85 0.84 2.36 3.06 1.62 3.30 2.80 (b) Why should we consider adjusted R² instead of R² when evaluating this model? O We should consider the adjusted ² instead of O We should consider the adjusted instead of O We should consider the adjusted ² instead of O We should consider the adjusted instead of 2.83 3.17 1.30 1.62 130 139 Use technology to calculate the P-value. (Round your answer to four decimal places.) P-value = 180 281 332 93 515 325 568 339 180 235 239 363 312 631 1248 651 306 (a) Fit a multiple regression model for predicting the volume (in ml) of a package based on its minimum width, maximum width, and elongation score. (Round your numerical values to two decimal places. Use x for minimum width, x₂ for the maximum width and x, for the elongation score.) ŷ = 320 310 247 204 1204 2329 because it takes into account the number of predictors used in the model. In this case the adjusted is noticeably less than ². because it does not take into account the number of predictors used in the model. In this case the adjusted ² is noticeably greater than 2. because it takes into account the number of predictors used in the model. In this case the adjusted 2 is noticeably greater than r². because it does not take into account the number of predictors used in the model. In this case the adjusted ² is noticeably less than ². 731 What can you conclude? O Reject H. We have convincing evidence that the multiple regression model is useful and can conclude that at least one of B₁, B₂ or 3 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 B₁, B₂ and ₂ are all 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 B₁, B₂ or 3 is not 0. O Reject H. We have convincing evidence that the multiple regression model is useful and can conclude that ₁, ₂ and ₂ are all not 0.
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