A national insurance organization wanted to study the consumption pattern of cigarettes in all 50 states and the District of Columbia

A national insurance organization wanted to study the consumption

pattern of cigarettes in all 50 states and the District of Columbia. The variables chosen for the study are:

-Age: Median age of a person living in a state.
-HS: Percentage of people over 25 years of age in a state who had completed high school.
-Income: Per capita personal income for a state (income in dollars).
-Black: Percentage of blacks living in a state.
-Female: Percentage of females living in a state.
-Price: Weighted average price (in cents) of a pack of cigarettes in a state.
-Sales: Number of packs of cigarettes sold in a state on a per capita basis.The data can be foundat
 http://www1.aucegypt.edu/faculty/hadi/RABE5/Data5/P088.txt.
Using the R programming answer the following questions at 5% level of significance discuss each. Below, specify the null and alternative hypotheses, the test used, and your conclusion using a 5% level of significance.


1. Test the hypothesis that the variable Female is not needed in the regression equation 
relating Sales to the six predictor variables.
2. Test the hypothesis that the variables Female and HS are not needed in the above 
regression equation.
3. Compute the 95% confidence interval for the true regression coefficient of the variable Income.
4. What percentage of the variation in Sales can be accounted for when Income is removed from the above regression equation? Explain.
5. What percentage of the variation in Sales can be accounted for by the three variables: 
Price, Age, and Income? Explain.
6. What percentage of the variation in Sales that can be accounted for by the variable 
Income, when Sales is regressed on only Income? Explain.