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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
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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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
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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