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3) You want to study the effects of disposable income, anti-smoking advertising and cigarette prices on the per capita consumption of cigarettes in US. You collect data on these variables across the 51 states over 20 years. You thus have 51x20=1,020 data points. For each state and year, you measure: Y=per capita consumption of cigarette (the fraction of the state population that smoked in that year); X1=per capital income in the state (in US$); X2=total expenditure in anti-smoking advertising in that state (in USS); and X3=average cigarette price in the state (in US$). You can then run a model: Y = Bo+Bi*X1+ B2*X+ B3* X3+ɛ Explain how you would test that the model is useful in predicting Y: How you would test the alternative hypothesis that you have at least one of the coefficients B1, B2 or ß3 is different from zero. (That is, the null is that all three coefficients are zero.) Use a significance level a=0.05.

3) You want to study the effects of disposable income, anti-smoking advertising and cigarette prices on the per capita consumption of cigarettes in US. You collect data on these variables across the 51 states over 20 years. You thus have 51x20=1,020 data points. For each state and year, you measure: Y=per capita consumption of cigarette (the fraction of the state population that smoked in that year); X1=per capital income in the state (in US$); X2=total expenditure in anti-smoking advertising in that state (in USS); and X3=average cigarette price in the state (in US$). You can then run a model: Y = Bo+Bi*X1+ B2*X+ B3* X3+ɛ Explain how you would test that the model is useful in predicting Y: How you would test the alternative hypothesis that you have at least one of the coefficients B1, B2 or ß3 is different from zero. (That is, the null is that all three coefficients are zero.) Use a significance level a=0.05.

ENGR.ECONOMIC ANALYSIS
ENGR.ECONOMIC ANALYSIS
14th Edition
ISBN:9780190931919
Author:NEWNAN
Publisher:NEWNAN
Chapter1: Making Economics Decisions
Section: Chapter Questions
Problem 1QTC
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3) You want to study the effects of disposable income, anti-smoking advertising and cigarette prices on the per capita consumption of cigarettes in US. You collect data on these variables across the 51 states over 20 years. You thus have 51x20=1,020 data points. For each state and year, you measure: Y=per capita consumption of cigarette (the fraction of the state population that smoked in that year); Xı=per capital income in the state (in US$); Xx=total expenditure in anti-smoking advertising in that state (in USS); and X3=average cigarette price in the state (in US$). You can then run a model: Y= Bo+Bi*X++ B2*X+ B3*X3+e Explain how you would test that the model is useful in predicting Y: How you would test the alternative hypothesis that you have at least one of the coefficients B1, ß2 or ß3 is different from zero. (That is, the null is that all three coefficients are zero.) Use a significance level a=0.05. (Again, there is no need to “run" the data. Just explain what you would do. Assume you have all data ready to go, and you have access to any statistical package.)
Transcribed Image Text:3) You want to study the effects of disposable income, anti-smoking advertising and cigarette prices on the per capita consumption of cigarettes in US. You collect data on these variables across the 51 states over 20 years. You thus have 51x20=1,020 data points. For each state and year, you measure: Y=per capita consumption of cigarette (the fraction of the state population that smoked in that year); Xı=per capital income in the state (in US$); Xx=total expenditure in anti-smoking advertising in that state (in USS); and X3=average cigarette price in the state (in US$). You can then run a model: Y= Bo+Bi*X++ B2*X+ B3*X3+e Explain how you would test that the model is useful in predicting Y: How you would test the alternative hypothesis that you have at least one of the coefficients B1, ß2 or ß3 is different from zero. (That is, the null is that all three coefficients are zero.) Use a significance level a=0.05. (Again, there is no need to “run" the data. Just explain what you would do. Assume you have all data ready to go, and you have access to any statistical package.)
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