The following table shows the output of a regression of selected S&P; 500 compan
ID: 1113387 • Letter: T
Question
The following table shows the output of a regression of selected S&P; 500 companies' net income in billions of dollars (the dependent variable) on their sales in billions of dollars (the independent variable) SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations 0.726492486 0.527791332 0.526571154 1444.608669 389 ANOVA Significance F 1902692213.7 902692213.7432.55293494.90343E-65 MS Regression Residual 387 807628057.7 2086894.206 388 1710320271 Coefficients Standard Errort Stat 4.18074218483.62471914 0.0499940950.960152886-160.2348801 168.5963645 0.0625783670.003008878 20.79790698 4.90343E-65 0.056662574 0.068494161 P-value Lower 95% Upper 95% Intercept SalesExplanation / Answer
a) slope coefficient of sales is 0.062578367. the positive value shows the positive relationship between net income and sales. Higher sales leads to higher net income. But the value of coefficient is very which implies that if sales increases by 1 unit net income increases by 0.0625 units only.
b) intercept= 4.18074... Means that if sales is 0 net income is still 4.18074....
c) estimated value of intercept does not make sense as with sales net income should be negative because of the cost of production incurred.
d) tstat of sales is 20.79 which is greater than critical t value 1.96, hence we can say coefficient is statistically significant. So answer is yes
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