We run a regression on data collected from employees of a firm: = 0…
Question Answered step-by-step We run a regression on data collected from employees of a firm: = 0… We run a regression on data collected from employees of a firm: ?? = ??0 + ??1??1 + ??2??2 + ??3??3 + ??· ??: salary in $1000; · ??1: years of education; · ??2: years of experience; · ??3: an indicator for being a union member, takes value 1 if is a union member, value 0 if not. Regression StatisticsR Square …………………….0.5113Adjusted R SquareStandard Error ……………3.6614Observations……………….40 ANOVA df SS MS FRegression 490.9441ResidualTotal 960.1414 Coefficient s Standard Error……. t Stat P-value Lower 95% ……Upper 95% Intercept 2.0575 3.2222 0.6385…… 0.5273 …….-4.4840 ………8.5989??1: education ………..0.4834 0.1464 3.3024 0.0022 0.1862 0.7805 ??2: experience 1.4825 0.6256 ??3: union member 1.1500 1.3031 0.8825 0.3835 -1.4954 3.7955 1) (2′) Use the information from the table to test for the overall significance of all independent variables at the 95% level. 2) (1′) Interpret the estimated coefficient in front of “education”, 0.4834. 3) (2′) Use the information from the table to test the following hypothesis at the 95% level ??0: ??2 < 1; ????: ??2 ? 1.4) (1') According to the point estimates, what is the predicted salary level of a union member with 12 years of education and 2 years of experience?5) (3') In the regression above, "education" is included as a numerical variable. How would you run the regression if you want to learn the relationship between "education level" and salary? There are three different levels of education among all employees: high school degree, college degree, and graduate degree. Explain how you would define new variables and write down the new regression model. Explain what each slope parameter related to education mean. Math Statistics and Probability STATS 110 Share QuestionEmailCopy link Comments (0)
