Reference no: EM132464339

The following data is part of a sample taken from the mortality tables of a life insurance company.  Data provide information on how life expectancy (dependent variable Y) relates to two independent variables:  

Weight (X₁ in pounds) and whether or not the individual is a smoker (X₂), where:

X2 = 0 if the individual is a nonsmoker, 1 if the individual is a smoker

Age (Y) Weight (X₁). Smoker (X₂)

59 253 1

 93 180 0

 70 201 1

 60 268 1

 70 152 0

 . . .

 etc. etc. etc.

The results of regression analysis, relating Y to X₁ and X₂ is shown below.

Regression Statistics

Multiple R 0.5983

R Square 0.3580

Adjusted R Square 0.3373

Standard Error 8.5599

Observations 65

ANOVA

df SS MS F Significance F

Regression 2 2533.19 1266.60 17.29 0.0000

Residual 62 4542.87 73.27

Total 64 7076.06

Coefficients Standard Error t Stat P-value

Intercept 92.8770 4.0964 22.6729 0.0000

Weight -0.0623 0.0247 -2.5208 0.0143

Smoker -6.2675 2.9096 -2.1541 0.0351

a. Can you Use the output shown above and write the regression equation.

Y = ___+/ - __X1 +/- ___X2 +/- ___X3

b. Work to Interpret the coefficients of the estimated regression equation.

c. At 95% confidence, can you determine which variables are significant and which are not.

d. At 95% confidence, test to determine if the regression model represents a significant relationship between the independent variables and the dependent variable.  (is the model significant?)

e. What is the life expectancy of a nonsmoker who weighs 150 pounds.

f. What is the life expectancy of a person who smokes 1 pack of cigarettes per day and weighs 150 pounds.

g.  What the life expectancy of a person who smokes 3 packs of cigarettes per day and weighs 150 pounds.