> model = lm(Data_Project$cig ~ Data_Project$age+Data_Project$hsize+Data_Project
ID: 3269138 • Letter: #
Question
> model = lm(Data_Project$cig ~ Data_Project$age+Data_Project$hsize+Data_Project$fam_inc+Data_Project$age+Data_Project$beerprice+Data_Project$cigprice)
> summary(model)
Call:
lm(formula = Data_Project$cig ~ Data_Project$age + Data_Project$hsize +
Data_Project$fam_inc + Data_Project$age + Data_Project$beerprice +
Data_Project$cigprice)
Residuals:
Min 1Q Median 3Q Max
-9.597 -5.461 -3.730 0.266 94.443
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 14.174563 2.471953 5.734 1.18e-08 ***
Data_Project$age -0.119862 0.019404 -6.177 8.41e-10 ***
Data_Project$hsize -0.338563 0.213941 -1.583 0.1137
Data_Project$fam_inc -0.017481 0.004461 -3.918 9.31e-05 ***
Data_Project$beerprice 0.246440 0.230481 1.069 0.2851
Data_Project$cigprice -0.999028 0.505246 -1.977 0.0482 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 9.86 on 1490 degrees of freedom
Multiple R-squared: 0.04211, Adjusted R-squared: 0.0389
F-statistic: 13.1 on 5 and 1490 DF, p-value: 1.662e-12
***Consider the data above retrieved from RStudio and answer the following questions. Please Explain Completely Referencing the Data)***
1)What is the effect of cigarette prices on smoking?
2)Do you think cigarettes and beer are complements or substitutes?
3)How do household size, family income and age affect cigarette smoking?
Explanation / Answer
1) What is the effect of cigarette prices on smoking?
The p-value for the coefficient of cigarette price is given as 0.0482 which is less than the level of significance or alpha value 0.05. So, we reject the null hypothesis that there is no any statistically significant effect of cigarette prices on the smoking. This means, there is sufficient evidence to conclude that there is a statistically significant effect of cigarette prices on the smoking.
2)Do you think cigarettes and beer are complements or substitutes?
The overall p-value of the model is given as 0.00 approximately which indicate that overall model is statistically significant. This implies that there is a statistically significant relationship exists between dependent variable or response variable smoking and independent variables age, size, income, beer price, cigarette price, etc. Cigarettes and beer are not complements or substitutes as there is no any inter-correlation exists between the two variables price of beer and price of cigarette. There is a absence of multicollinearity problem.
3)How do household size, family income, and age affect cigarette smoking?
The p-value for the coefficient for household size is given as 0.1137 which is greater than the level of significance or alpha value 0.05, so we do not reject the null hypothesis that there is no any statistically significant effect of household size on the cigarette smoking.
The p-value for the coefficient of family income is given as 0.0000931 which is less than the given level of significance or alpha value 0.05, so we reject the null hypothesis that there is no any statistically significant effect of the variable family income on the cigarette smoking. There is sufficient evidence to conclude that there is significant effect of family income on the cigarette smoking.
The p-value for the variable age is given as 0.00 approximately which is less than the level of significance or alpha value 0.05, so we reject the null hypothesis that there is no any statistically significant effect of the age on the cigarette smoking. This means, there is sufficient evidence to conclude that there is statistically significant effect of the age on the cigarette smoking.
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.