Can some one answer the questions below with the information on regression stats.

Obesity(f)= Physical Inactivity , fast food SUMMARY OUTPUT

Regression Statistics

Multiple R 0.77074844

R Square 0.59405315

Adjusted R Square 0.5771387

Standard Error 2.61921796

Observations 51

ANOVA

df SS MS F Significance F

Regression 2 481.8819397 240.94097 35.12104 4.01E-10

Residual 48 329.2945309 6.86030273

Total 50 811.1764706

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%

Intercept 9.18173273 2.426650963 3.78370556 0.000429 4.302624 14.06084 4.302624 14.06084 Physical Inactivity 0.59080537 0.093694177 6.30567864 8.54E-08 0.402421 0.77919 0.402421 0.77919 Fast Food per cap/ 10K people 1.67944376 0.617975456 2.71765447 0.009119 0.436921 2.921967 0.436921 2.921967

6) Write the regression (prediction) equation:

Dep_Var = Intercept + c1 * Ind_Var_1 + c2 * Ind_Var_2 + c3* Ind_Var_3

7) Identify and interpret the adjusted R2 (one paragraph):

• Define adjusted R2.
• What does the value of the adjusted R2 reveal about the model?
• If the adjusted R2 is low, how has the choice of independent variables created this result?

8) Identify and interpret the F test (one paragraph):

• Using the p-value approach, is the null hypothesis for the F test rejected or not rejected? Why or why not?
• Interpret the implications of these findings for the model.

9) Identify and interpret the t tests for each of the coefficients (one separate paragraph for each variable, in numerical order):