The R-output (to the right) represents the result of linear regression model, where the explanatory varia-...

 

Transcribed Image Text:

The R-output (to the right) represents the result of linear regression model, where the explanatory varia- ble is the car speed (in mph) and the response is the distance to stop (in ft). (a) Find estimated regression coefficients. (b) Test Ho B = 0 vs H B 0 at 1% signif. level. (c) What is the estimated stopping distance for car that drives 10 mph? call: In(formula cars) Residuals: Min 10 Median -7.5293 -2.1550 0.3615 2.4377 Coefficients: 30 Max 6.4179 Estimate Std. Error t value Pr(>|t) (Intercept) 8.28391 0.87438 dist --- 0.16557 0.01749 9.474 1.44e-12 *** 9.464 1.49e-12 *** signif. codes: 0.001 0.01 0.05 0.11 Residual standard error: 3.156 on 48 degrees of freedom Multiple R-squared: 0.6511, Adjusted R-squared: 0.6438 F-statistic: 89.57 on 1 and 48 DF, p-value: 1.49e-12 The R-output (to the right) represents the result of linear regression model, where the explanatory varia- ble is the car speed (in mph) and the response is the distance to stop (in ft). (a) Find estimated regression coefficients. (b) Test Ho B = 0 vs H B 0 at 1% signif. level. (c) What is the estimated stopping distance for car that drives 10 mph? call: In(formula cars) Residuals: Min 10 Median -7.5293 -2.1550 0.3615 2.4377 Coefficients: 30 Max 6.4179 Estimate Std. Error t value Pr(>|t) (Intercept) 8.28391 0.87438 dist --- 0.16557 0.01749 9.474 1.44e-12 *** 9.464 1.49e-12 *** signif. codes: 0.001 0.01 0.05 0.11 Residual standard error: 3.156 on 48 degrees of freedom Multiple R-squared: 0.6511, Adjusted R-squared: 0.6438 F-statistic: 89.57 on 1 and 48 DF, p-value: 1.49e-12