Call: lm(formula = Profit ~ ., data = dataset)
Residuals: Min 1Q Median 3Q Max -33504 -4736 90 6672 17338
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.013e+04 6.885e+03 7.281 4.44e-09 ***
R.D.Spend 8.060e-01 4.641e-02 17.369 < 2e-16 ***
Administration -2.700e-02 5.223e-02 -0.517 0.608
Marketing.Spend 2.698e-02 1.714e-02 1.574 0.123
State2 1.988e+02 3.371e+03 0.059 0.953
State3 -4.189e+01 3.256e+03 -0.013 0.990
Signif. codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 9439 on 44 degrees of freedom Multiple R-squared: 0.9508, Adjusted R-squared: 0.9452 F-statistic: 169.9 on 5 and 44 DF, p-value: < 2.2e-16
mlr=lm(Profit~R.D.Spend+Marketing.Spend+Administration, data = dataset) summary(mlr)
Call: lm(formula = Profit ~ R.D.Spend + Marketing.Spend + Administration, data = dataset)
Residuals: Min 1Q Median 3Q Max -33534 -4795 63 6606 17275
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.012e+04 6.572e+03 7.626 1.06e-09 ***
R.D.Spend 8.057e-01 4.515e-02 17.846 < 2e-16 ***
Marketing.Spend 2.723e-02 1.645e-02 1.655 0.105
Administration -2.682e-02 5.103e-02 -0.526 0.602
Signif. codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 9232 on 46 degrees of freedom Multiple R-squared: 0.9507, Adjusted R-squared: 0.9475 F-statistic: 296 on 3 and 46 DF, p-value: < 2.2e-16
mlr=lm(Profit~R.D.Spend+Marketing.Spend,data = dataset) summary(mlr)
Call: lm(formula = Profit ~ R.D.Spend + Marketing.Spend, data = dataset)
Residuals: Min 1Q Median 3Q Max -33645 -4632 -414 6484 17097
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.698e+04 2.690e+03 17.464 <2e-16 ***
R.D.Spend 7.966e-01 4.135e-02 19.266 <2e-16 ***
Marketing.Spend 2.991e-02 1.552e-02 1.927 0.06 .
Signif. codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 9161 on 47 degrees of freedom Multiple R-squared: 0.9505, Adjusted R-squared: 0.9483 F-statistic: 450.8 on 2 and 47 DF, p-value: < 2.2e-16
mlr=lm(Profit~R.D.Spend,data = dataset) summary(mlr)
Call: lm(formula = Profit ~ R.D.Spend, data = dataset)
Residuals: Min 1Q Median 3Q Max -34351 -4626 -375 6249 17188
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.903e+04 2.538e+03 19.32 <2e-16 ***
R.D.Spend 8.543e-01 2.931e-02 29.15 <2e-16 ***
Signif. codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 9416 on 48 degrees of freedom Multiple R-squared: 0.9465, Adjusted R-squared: 0.9454 F-statistic: 849.8 on 1 and 48 DF, p-value: < 2.2e-16