a) t values will be the ratio of Coefficient and SE and then, p - value will be two tailed value corresponding to that t at 33 d.f. Hence,
The complete table will be:
b) t value = 2.733
c) Option A is correct.
A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used...
A regression model to predict Y, the state burglary rate per 100,000 people for 2005, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies, X3 = 2004 federal expenditures per capita (a leading predictor), and X4 = 2005 high school graduation percentage. (a) Fill in the values in the table given here for a two-tailed test at α = 0.01 with 31 d.f. (Negative values should be indicated by a minus...
A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies per 1,000 people, X3 = 2004 federal expenditures per capita, and X4 = 2005 high school graduation percentage. Predictor Coefficient Intercept 4,579.5465 AgeMed -27.292 Bankrupt 19.5612 FedSpend -0.0264 HSGrad% -27.5839 (a) Write the fitted regression equation. (Round your answers to 4 decimal places. Negative values should be...
A regression model to predict Y, the state-by-state 2005 burglary crime rate per 100,000 people, used the following four state predictors: X1 = median age in 2005, X2 = number of 2005 bankruptcies per 1,000 people, X3 = 2004 federal expenditures per capita, and X4 = 2005 high school graduation percentage. Predictor Coefficient Intercept 4,304.4610 AgeMed -26.903 Bankrupt 20.8921 FedSpend -0.0312 HSGrad% -29.1815 (a) Write the fitted regression equation. (Round your answers to 4 decimal...
Observations are taken on sales of a certain mountain bike in 21 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit). (a) Fill in the values in the table given here. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round...
Observations are taken on sales of a certain mountain bike in 30 sporting goods stores. The regression model was Y = total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit). (a) Fill in the values in the table given here. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round...