Explanation:
What these numbers for the ME’s and the elasticities mean:
ME of X on Y implies that with each additonal unit of X, Y increments by 0.03 units.
ME of Z on Y implies that with each extra unit of Z at Z=18, Y increments by 19.5 units.
At X = 2.5 and Z = 18,
Versatility of Y as for X implies that with one percent expansion in X, Y increments by 0.0003956 percent.
Versatility of Y as for Z implies that with one percent expansion in Z, Y increments by 1.8515 percent.
Question 3: Consider the following estimated quadratic regression model: Ý, = 0.5 + 0.03X, + 152i...
Consider the following estimated regression model relating annual salary to years of education and work experience. Estimated Salary=10,550.60+2781.63(Education)+870.46(Experience)Estimated Salary=10,550.60+2781.63(Education)+870.46(Experience) Suppose an employee with 44 years of education has been with the company for 88 years (note that education years are the number of years after 8th8th grade). According to this model, what is his estimated annual salary?
10. You have estimated the following simple regression model: Iny=3+4 In x What is the estimated elasticity of y with respect to x, when x = 5? (Recall: € = alny = dyr]. a) 3 b) 4 c) 5 d) 4 In x
Help me with two questions PLEASE:
QUESTION 1
Regarding a regression model, all of the following can be
negative except the
a. correlation coefficient
b. coefficient of “x” in the regression equation
c. coefficient of determination
d. y-intercept in the regression equation
QUESTION 2
Regression analysis was performed on a time series containing 5
years of quarterly sales. The sales data contains both trend and
seasonal effects. The following estimated regression equation was
obtained.
The sales forecast...
Question 2 1 pts Suppose that we wish to built the following multiple regression model: Ý; = ßo + Ê, Xi1 + ,Xj2 where Y = mathematics exam score, X 1 =number of hours spent studying, X 2 =number of hours spent playing video games. Suppose we know that the number of hours spent studying is directly inversely proportional to the number of hours spend playing video games. Which of the following would be true, We cannot obtain the coefficients...
Consider the following data for two variables, x and y. (a) Develop an estimated regression equation for the data of the form ý = bo + 5,x. (Round bo to two decimal places and b, to three decimal places.) Comment on the adequacy of this equation for predicting y. (Use a = 0.05.) The high p-value and low coefficient of determination indicate that the equation is inadequate. The high p-value and high coefficient of determination indicate that the equation is...
QUESTION 1 Consider the following OLS regression line (or sample regression function): wage =-2.10+ 0.50 educ (1), where wage is hourly wage, measured in dollars, and educ years of formal education. According to (1), a person with no education has a predicted hourly wage of [wagehat] dollars. (NOTE: Write your answer in number format, with 2 decimal places of precision level; do not write your answer as a fraction. Add a leading minus sign symbol, a leading zero and trailing...
3. Suppose that you are provided with the following estimated regression model for academic performance of students in your district: Test score = 686.0-1.10 x Student teacher ratio-0.650 x Percentage of English students, (8.7) (0.43) (0.031) where the numbers in parentheses are standard errors. (a) Construct 95% confidence intervals for the true regression coefficients of Student teacher ratio and Percentage of English-students. How do you interpret these confidence intervals?
need help with c d and e
3. (25 points) Consider a regression model that relates the proportion of a household's bud- get spent on alcohol WALC to total expenditure TOTEXP, age of the household head AGE, and the number of children in the household NK. Followings are the regression output after the estimation, WALC- 0.0091 +0.0276l(TOTEXP) +a xAGE -00133NK (0.019) (0.0002) (0.0033) (6.6086 6.9624) -4.0750 where n 2000, SSR-5.7529, () are the standard errors, and (-J are the correspond-...
Consider the following estimated models: Model 1: y-16 + 5.42x Model 2: y-29 + 29 In(x) Model 3: In(y) 2.0+0.10x, se 0.06 Model 4: In(y -2.4+0.36 In(; se 0.12 b. For each model, what is the predicted change in y when x increases by 4%, from 10 to 10.47 (Do not round intermediate calculations. Round final answers to 2 decimal places.) units units percent percent. Model 1:y increases Model 2: ý increases Model 3: increases Model 4:y increases by by...
Consider the following regression model: Xi = Bo + Bixi + y; where yi is individual i's University GPA and xi is the individual's high school grades. a. What do you think is in ui? Do you think E[ulx) = 0? Suggest a variable that you think might affect University GPA that isn't included in the regression equation but should be. c. What sign of bias would you expect in an OLS regression of y on x? Briefly explain. d....