What does rejection of Ho: p = 0 imply for the regression equation ŷ = bo + bịx? Explain in 1 - 2 complete sentences.
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A: *Answer:
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- Please help me understand question and how to solve. A researcher at a large company has collected data on the beginning salary and current salary of 48 randomly selected employees. The least-squares regression equation for predicting their current salary from their beginning salary is Y=-2500 + 2.1X. Where Y is the current salary and X is the beginning salary. Question: Jay started working for the company earning $ 30,000. He currently earns $60,000. What is the residual for Jay (assuming no extrapolation error)?What do we mean when we say that a multiple regression model is a multiple linear regression model? What does “linear” mean here? Can we allow any “higher-order terms”? Explain.What are the assumptions of multiple linear regressions only?
- also compute the regression equation in which you predict Y using X as the predictor variableWhat is the null hypothesis to test the significance of the slope in a regression equation? Multiple Choice Ho:B 20 Ho: Bs0 O Ho: B = 0 Ho: B 0A 1 ROAA (%) Efficiency Ratio (%) 2 1.04 39.93 3 57.75 4 81.4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0.68 7.27 1.08 0.72 0.92 0.79 1.04 1.76 1.07 1.37 0.93 0.66 1.72 1.5 0.59 2.12 1.11 1.45 1.06 B A 53.49 71.08 65.41 68.07 68.14 68.1 64.82 48.58 63.1 59.16 49.93 54.7 81.6 75.21 69.82 49.47 57.09 с Total Risk-Based Capital (%) 17.04 13.88 27.77 18.31 14.66 14.04 13.38 16.8 16.69 13.86 12 18.65 19.76 17.69 26.6 15.08 14.55 17.5 16.03 14.62 D E F G H |
- Two variable are found to have a strong negative linear correlation. Pick the regression equation that best fits this scenario. y=0.82x−28 ˆy=0.32x−28 y= -0.82x+28 ˆy= -0.32x+28If the estimated intercept of the regression equation is negative, we can say the estimated correlation coefficient between the two variables is also negative. O True O FalseWhen should a regression model not be used to make a prediction?
- How to know if obtaining a regression equation for the data appear reasonable?A box office analyst seeks to predict opening weekend box office gross for movies. Toward this goal, the analyst plans to use online trailer views as a predictor. For each of the 66 movies, the number of online trailer views from the release of the trailer through the Saturday before a movie opens and the opening weekend box office gross (in millions of dollars) are collected and stored in the accompanying table. A linear regression was performed on these data, and the result is the linear regression equation Yi=−0.840+1.4108Xi. Determine the coefficient of determination,r2,and interpret its meaning. Determine the standard error of the estimate. How useful do you think this regression model is for predicting opening weekend box office gross? Can you think of other variables that might explain the variation in opening weekend box office gross?A sports statistician was interested in the relationship between game attendance (in thousands) and the number of wins for baseball teams. Information was collected on several teams and was used to obtain the regression equation ý = 4.9 + 15.2, where x represents attendance (in thousands) and ý is the predicted number of wins. Which statement best describes the meaning of the slope of the regression line? For each increase in attendance by 1,000, the predicted number of wins increases by 4.9. O For each increase in attendance by 1,000, the predicted number of wins increases by 15.2. O For each increase in the number of wins by 1, the predicted attendance increases by 4,900. O For each increase in the number of wins by 1, the predicted attendance increases by 15,200.
