Researchers present data from an early study that examined the possible link between air pollution and mortality. In this study the variables are:

The response y=MORT is the total age - adjusted mortality from all causes, in deaths per 100,000 population. The regressor x₁ :PRECIP is the mean annual precipitat ion (in inches), x₂ :EDUC is the median number of school years completed for persons of age 25 years or older, x₃ :NONWHITE is the percentage of the 1960 population that is nonwhite, x₄ :NOX is the relative pollution potential of oxides of nitrogen, and x₅:SO₂ is the relative pollution potential of sulfur dioxide. " Relative pollution potential " is the product of the tons emitted per day per square kilometer and a factor correcting the SMSA dimensions and exposure.

Use the SAS output to answer the following questions.

(a)Write the fitted regression model relating y to the other variables.

(b) Specify appropriate null and alternate hypotheses for testing the adequacy of the overall model. Report values for the F-statistic, degrees of freedom, and p-value, and state the conclusion of this test.

(c) Test the partial effect SO₂, and interpret.

(d) Predict the Mort product when x₁ =35.0, x₂ = 11 , x₃ =15 , x₄ =20, x₅ = 60.

(e). Report the R² value and give an interpretation of this value in the context of the problem.

The REG Procedure Model: MODELI Dependent Variable: y Number of Observations Read 60 Number of Observations Used 60 Analysis of Variance Sum of Mean Source DF Squares Square F Value Pr > F Model 5 153946 30789 22.37 <.0001 error corrected total root mse r-square dependent mean adj r-sq coeff var parameter estimates standard variable df estimate t value pr> t Intercept 1 996.42015 91.66874 10.87 <.0001 x1 x2 x3 x4 x5>