Shown below are data on per capita personal consumption, paper consumption, fish consumption, and gasoline consumption for 11 countries. Use the data to develop a multiple regression model to predict per capita personal consumption by the consumption of paper, fish, and gasoline. Discuss the output and pay particular attention to the F test and thet tests. Per Capita Рaper Fish Gasoline Personal Consumption (kilograms (U.S. $) Consumption Consumption Consumption (kilograms per person) (liters per person) Country per person) Bangladesh 836 1 10 2 Greece 3,145 85 24 394 Italy 21,785 204 22 368 Japan 37,931 250 64 447 Kenya 276 16 Norway 1,913 156 51 477 Philippines 2,195 19 30 43 Portugal 3,154 116 60 257 U.K. 19,539 207 20 460 U.S. 109,521 308 21 1,624 Venezuela 622 27 18 528 *(Round your answers to 2 decimal places, e.g. 1.75.) **(Round your answers to 4 decimal places, e.g. 1.7589.) ***(Round your answers to 3 decimal places, e.g. 1.757.) The regression model is: Per Capita Prsonal Consumption = * Paper Consumption - Fish Consumption + * Gasoline Consumption. This model yields an F = * with p-value = . Thus, there is overall significance at a = .01. One of the three predictors is significant. Gasoline Consumption has at = 2.66 with p- value of *** which is statistically significant at a = .05. The p-values of the t statistics for the other two nredictors are insignificant indicating that a model with just Gasoline Consumption as a single predictor nearly as strong. might be Appendix A Statistical Tables
Shown below are data on per capita personal consumption, paper consumption, fish consumption, and gasoline consumption for 11 countries. Use the data to develop a multiple regression model to predict per capita personal consumption by the consumption of paper, fish, and gasoline. Discuss the output and pay particular attention to the F test and thet tests. Per Capita Рaper Fish Gasoline Personal Consumption (kilograms (U.S. $) Consumption Consumption Consumption (kilograms per person) (liters per person) Country per person) Bangladesh 836 1 10 2 Greece 3,145 85 24 394 Italy 21,785 204 22 368 Japan 37,931 250 64 447 Kenya 276 16 Norway 1,913 156 51 477 Philippines 2,195 19 30 43 Portugal 3,154 116 60 257 U.K. 19,539 207 20 460 U.S. 109,521 308 21 1,624 Venezuela 622 27 18 528 *(Round your answers to 2 decimal places, e.g. 1.75.) **(Round your answers to 4 decimal places, e.g. 1.7589.) ***(Round your answers to 3 decimal places, e.g. 1.757.) The regression model is: Per Capita Prsonal Consumption = * Paper Consumption - Fish Consumption + * Gasoline Consumption. This model yields an F = * with p-value = . Thus, there is overall significance at a = .01. One of the three predictors is significant. Gasoline Consumption has at = 2.66 with p- value of *** which is statistically significant at a = .05. The p-values of the t statistics for the other two nredictors are insignificant indicating that a model with just Gasoline Consumption as a single predictor nearly as strong. might be Appendix A Statistical Tables
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
q12
![Shown below are data on per capita personal consumption, paper consumption, fish consumption, and gasoline
consumption for 11 countries. Use the data to develop a multiple regression model to predict per capita personal
consumption by the consumption of paper, fish, and gasoline. Discuss the output and pay particular attention to the F
test and the t tests.
Per Capita
Раper
Fish
Gasoline
Personal
Consumption (kilograms
(U.S. $)
Consumption Consumption Consumption
(kilograms
per person)
(liters
Country
per person)
per person)
Bangladesh
836
1
10
2
Greece
3,145
85
24
394
Italy
21,785
204
22
368
Japan
37,931
250
64
447
Kenya
276
4
5
16
Norway
1,913
156
51
477
Philippines
2,195
19
30
43
Portugal
3,154
116
60
257
U.K.
19,539
207
20
460
U.S.
109,521
308
21
1,624
Venezuela
622
27
18
528
*(Round your answers to 2 decimal places, e.g. 1.75.)
**(Round your answers to 4 decimal places, e.g. 1.7589.)
***(Round your answers to 3 decimal places, e.g. 1.757.)
The regression model is: Per Capita Prsonal Consumption =
Paper Consumption -
Fish Consumption +
* Gasoline Consumption.
This model yields an F =
* with p-value =
**. Thus, there
is overall significance at a = .01. One of the three predictors is significant. Gasoline Consumption has a t = 2.66 with p-
value of
which is statistically significant at a = .05. The p-values of the t statistics for
the other two predictors are insignificant indicating that a model with just Gasoline Consumption as a single predictor
nearly as strong.
might be
Appendix A Statistical Tables
might not](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Fdee32018-85d1-483d-8de1-562067fcba2d%2Fe23765ea-87d2-4bb4-b6fc-e2f84d8f83a3%2F2xeoxkk_processed.png&w=3840&q=75)
Transcribed Image Text:Shown below are data on per capita personal consumption, paper consumption, fish consumption, and gasoline
consumption for 11 countries. Use the data to develop a multiple regression model to predict per capita personal
consumption by the consumption of paper, fish, and gasoline. Discuss the output and pay particular attention to the F
test and the t tests.
Per Capita
Раper
Fish
Gasoline
Personal
Consumption (kilograms
(U.S. $)
Consumption Consumption Consumption
(kilograms
per person)
(liters
Country
per person)
per person)
Bangladesh
836
1
10
2
Greece
3,145
85
24
394
Italy
21,785
204
22
368
Japan
37,931
250
64
447
Kenya
276
4
5
16
Norway
1,913
156
51
477
Philippines
2,195
19
30
43
Portugal
3,154
116
60
257
U.K.
19,539
207
20
460
U.S.
109,521
308
21
1,624
Venezuela
622
27
18
528
*(Round your answers to 2 decimal places, e.g. 1.75.)
**(Round your answers to 4 decimal places, e.g. 1.7589.)
***(Round your answers to 3 decimal places, e.g. 1.757.)
The regression model is: Per Capita Prsonal Consumption =
Paper Consumption -
Fish Consumption +
* Gasoline Consumption.
This model yields an F =
* with p-value =
**. Thus, there
is overall significance at a = .01. One of the three predictors is significant. Gasoline Consumption has a t = 2.66 with p-
value of
which is statistically significant at a = .05. The p-values of the t statistics for
the other two predictors are insignificant indicating that a model with just Gasoline Consumption as a single predictor
nearly as strong.
might be
Appendix A Statistical Tables
might not
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