Suppose you are interested in studying the factors that influence wages. You plan on using a multiple regression model with k=3 explanatory variables. In particular, you plan on estimating: wageˆ=β0ˆ+β1ˆeduc+β2ˆexper+β3ˆage where wage = hourly wage in dollars educ = years of education exper = years of work experience age = age, in years An alternative way of estimating β3ˆ would be to regress wage on ri3ˆ, (wagei=β0+β1ri3ˆ), where ri3ˆ are the residuals from a regression of . Suppose the following represents a simple regression model of wage on educ. wage∼=β0∼+β1∼educ where wage = hourly wage in dollars educ = years of education True or False: If the partial effects of exper on wage and age on wage are both zero, then β1ˆ will not be the same as β1∼. True False1ˆx1+⋅ ⋅ ⋅+βkˆxk Writing the OLS regression line in terms of changes yields . Suppose that Δx2 through Δxk are all equal to zero. Then the change in the explained variable yˆ can be written as .

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20% of 120 is 24. if you subtract 24 from 120 you get 96

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answer: a video game has three difficulty levels: easy, medium, and expert. the game's scoring works in such a way that a player has to score a fixed number of points to advance to the next level, and then the scoring starts over. the total score needed to clear all three difficulty levels is 7,500. two times the number of points needed to clear the easy level is 500 more than the number of points needed to clear the medium level. twice the number of points needed to clear the medium difficulty level is 1,500 more than the number of points needed to clear the expert level. if x, y, and z represent the easy, medium, and expert levels, respectively, and a is the coefficient matrix of the system of equations modeling this situation, identify the inverse matrix, a-1, and the solution matrix, x, of the system of equations.

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rauschg

rauschg · hand

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the answer is 13 cm