The following estimated regression equation is based on 10 observations was presented. ŷ= 29.1270 +0.5906z1 +0.498022 Here SST = 6,885.875, SSR = 6,231.500, sb, 0.0728, and s= 0.0540. a. Compute MSR and MSE (to 3 decimals). MSR= MSE: = b. Compute F and perform the appropriate F test (to 2 decimals). Use a = 0.05. Use the F table. F= The p-value is Select your answer - At a = 0.05, the overall model is-Select your answer - ✓ c. Perform a t test for the significance of B₁ (to 2 decimals). Use a = 0.05. Use the t table. t₁ = The p-value is Select your answer - At a = 0.05, there is-Select your answer-relationship between y and ₁. d. Perform a t test for the significance of B₂ (to 2 decimals). Use a = 0.05. Use the t table. to The p-value is - Select your answer - At a= 0.05, there is - Select your answer relationship between y and #2.

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y). The results of the regression were: y=ax+b a=-0.971 b=21.794 r²-0.872356 r=-0.934 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)

An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:.   Summary measures       Multiple R 0.9689       R-Square 0.9387       Adj R-Square 0.9212       StErr of Estimate 72.218                 Regression coefficients         Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.

A regression was run to determine if there is a relationship between hours of TV watched per day (xx) and number of situps a person can do (yy). The results of the regression were: y=ax+ba=-1.392b=32.952r2=0.527076r=-0.726Use this to predict the number of situps a person who watches 2 hour(s) of TV can do, and please round your answer to a whole number.

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-1.34 b=36.954 r2=0.966289 r=-0.983 Use this to predict the number of situps a person who watches 5 hours of TV can do (to one decimal place)

A regression was run to determine if there is a relationship between hours of TV watched per day (x) and number of situps a person can do (y).The results of the regression were:y=ax+b a=-0.667 b=26.552 r2=0.677329 r=-0.823 Use this to predict the number of situps a person who watches 12 hours of TV can do (to one decimal place)