Multiple Regression Problem Set I Using the Motor Trend Cars

Multiple Regression Problem Set I

Using the Motor Trend Cars Data Set, you would like to determine if there is a relationship between MPG (miles per gallon) and specific variables included in the data set.

a. Develop a correlation matrix using MPG (miles per gallon), HP (horsepower), WT (weight). Is the correlation between the variables significant or not? Conduct a test for all correlations; that is for MPG v. HP; MPG v. WT; HP v. WT. Use a level of significance of 0.05

b. Fit a multiple regression model using MPG (miles per gallon) as the dependent variable and HP (horsepower), and WT (weight) as the independent variables.

c. Is the overall regression model significant? Conduct the appropriate hypothesis tests for the significance of the overall regression model. Use a 0.05 level of significance.

d. Are the individual independent variables significant? Conduct a hypothesis tests for the significance of each independent variable at the= 0.05 level of significance.

e. What proportion of the variation in MPG is explained by the independent variables HP and WT?

f. Graph the residuals from the regression you developed in part (a). Do the regression assumptions appear to be appropriate given the residual plots?

data:

mpg cyl disp hp drat wt qsec vs am gear carb
Mazda RX4 21 6 160 110 3.9 2.62 16.46 0 1 4 4
Mazda RX4 Wag 21 6 160 110 3.9 2.875 17.02 0 1 4 4
Datsun 710 22.8 4 108 93 3.85 2.32 18.61 1 1 4 1
Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
Hornet Sportabout 18.7 8 360 175 3.15 3.44 17.02 0 0 3 2
Valiant 18.1 6 225 105 2.76 3.46 20.22 1 0 3 1
Duster 360 14.3 8 360 245 3.21 3.57 15.84 0 0 3 4
Merc 240D 24.4 4 146.7 62 3.69 3.19 20 1 0 4 2
Merc 230 22.8 4 140.8 95 3.92 3.15 22.9 1 0 4 2
Merc 280 19.2 6 167.6 123 3.92 3.44 18.3 1 0 4 4
Merc 280C 17.8 6 167.6 123 3.92 3.44 18.9 1 0 4 4
Merc 450SE 16.4 8 275.8 180 3.07 4.07 17.4 0 0 3 3
Merc 450SL 17.3 8 275.8 180 3.07 3.73 17.6 0 0 3 3
Merc 450SLC 15.2 8 275.8 180 3.07 3.78 18 0 0 3 3
Cadillac Fleetwood 10.4 8 472 205 2.93 5.25 17.98 0 0 3 4
Lincoln Continental 10.4 8 460 215 3 5.424 17.82 0 0 3 4
Chrysler Imperial 14.7 8 440 230 3.23 5.345 17.42 0 0 3 4
Fiat 128 32.4 4 78.7 66 4.08 2.2 19.47 1 1 4 1
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.9 1 1 4 1
Toyota Corona 21.5 4 120.1 97 3.7 2.465 20.01 1 0 3 1
Dodge Challenger 15.5 8 318 150 2.76 3.52 16.87 0 0 3 2
AMC Javelin 15.2 8 304 150 3.15 3.435 17.3 0 0 3 2
Camaro Z28 13.3 8 350 245 3.73 3.84 15.41 0 0 3 4
Pontiac Firebird 19.2 8 400 175 3.08 3.845 17.05 0 0 3 2
Fiat X1-9 27.3 4 79 66 4.08 1.935 18.9 1 1 4 1
Porsche 914-2 26 4 120.3 91 4.43 2.14 16.7 0 1 5 2
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.9 1 1 5 2
Ford Pantera L 15.8 8 351 264 4.22 3.17 14.5 0 1 5 4
Ferrari Dino 19.7 6 145 175 3.62 2.77 15.5 0 1 5 6
Maserati Bora 15 8 301 335 3.54 3.57 14.6 0 1 5 8
Volvo 142E 21.4 4 121 109 4.11 2.78 18.6 1 1 4 2

Solution

a) Develop a correlation matrix using MPG (miles per gallon), HP (horsepower), WT (weight). Is the correlation between the variables significant or not? Conduct a test for all correlations; that is for MPG v. HP; MPG v. WT; HP v. WT. Use a level of significance of 0.05

Sol) Correlation between MPG v. HP

from excel

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Hence Correlation between  MPG v. HP is-0.77617

Now Correlation between MPG v. WT

from excel

Hence Correlation between  MPG v. WT is-0.8677

Now Correlation between  HP v. WT.

from excel

Hence Correlation between   HP v. WT. is 0.6587

b) Fit a multiple regression model using MPG (miles per gallon) as the dependent variable and HP (horsepower), and WT (weight) as the independent variables.

Y=a+b(HP)+c(WT)

By using Excel

From above anaysis

The fitted regression model is Y(MPG) = 37.227+(-0.03177)*hp+(-3.3878)* wt

c) Since P<alpha hence we can say that regression model is significant

d) P value for Independent variables

p value for hp is 0.001

p<0.05 hence hp is significant

similarly p value for wt is 0.0000012

p<0.05 hence wt is significant

e) proportion of the variation in MPG is explained by the independent variables HP and WT is 83% (Using R square value)

mpg hp
mpg 1
hp -0.77617

1

Multiple Regression Problem Set I Using the Motor Trend Cars Data Set, you would like to determine if there is a relationship between MPG (miles per gallon) and
Multiple Regression Problem Set I Using the Motor Trend Cars Data Set, you would like to determine if there is a relationship between MPG (miles per gallon) and

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