please show your explanation thanks!
Ans a ) from the output of the regression model
the value of the coefficient of determination is 0.8391
about 83.91 % variability in mpg is explained by the model.
Ans b ) from the output and the p-value of the quarter-mile time variable is 0.00242
since p-value for this variable is less than 0.05 so these this predictor variable is statistically significant
please show your explanation thanks! ## ## Call: ## Im(formula = mpg ~ disp + hp...
Please show full details steps for better understanding. Thank you. Regression Coefficients Estimates Model formula: mpg - cyl + disp + hp + am Term Coefficient Estimate Standard Error t Value (Intercept) 30.476 2.8655 10.636 cyl -0.8345 0.75709 -1.1022 disp -0.0077447 0.010716 -0.72272 Pr > It! 3.7246e-11 0.28008 0.47607 hp -0.032962 0.015614 -2.1111 0.044166 am 3.4453 1.4539 2.3697 0.025205 Model Summary: Coefficient of Determination (R-Squared) Model formula: mpg - cyl + disp + hp + am Residual Standard Error DF...
UESTION 7 Fuel efficiency in auto-mobiles can be influences by a number of characteristics. See the linear regression output below and answer the following questions Results of linear regression analysis are shown below: Call: lm (formula = mpg ~ ., data = auto-mpg) Residuals: Min 1Q Median 3Q Max -8.6927-2.3864 -0.0801 2.0291 14.3607 Coefficients: Estimate Std. Error t value Pr>Itl) (Intercept) -1.454e+01 4.764e+00 -3.051 0.00244* cyl disp hp gvw accel year -3.299e-01 3.321e-01 -0.993 0.32122 7.678e-03 7.358e-03 1.044 0.29733 -3.914e-04...
1. For each of the following regression models, write down the X matrix and 3 vector. Assume in both cases that there are four observations (a) Y BoB1X1 + B2X1X2 (b) log Y Bo B1XiB2X2+ 2. For each of the following regression models, write down the X matrix and vector. Assume in both cases that there are five observations. (a) YB1XB2X2+BXE (b) VYBoB, X,a +2 log10 X2+E regression model never reduces R2, why 3. If adding predictor variables to a...