HeipA regression of average weekly earnings (AWE, measured in dollars) on age (measured in years) using a random sample ofcollege-educated full-time workers aged 25-65 yields the following:AWE = 647.9310 +8.9280 × Age, R2 = 0.021, SER=580.4.The coefficientshows the marginal effect of Age on AWE; that is, AWE is expected to increase by $for each additional yearof age.is the intercept of the regression line. It determines the overall level of the line.(Round your responses to four decimal places.)The standard error of the regression (SER) is 580.4. What are the units of measurement for the SER?O A. Dollars.O B. Dollars per year.C. Unit-free.O D. Dollars per week.The regression R is 0.021. What are the units of measurement for the R2?O A. Dollars per year.O B. Dollars.Click to select your answer(s).W0正e to search The regression R is 0.021. What are the units of measurement for the R2?O A. Dollars per year.OB. DollarsO C. Unit-free.O D. Dollars per week.What is the regression's predicted earnings for a 25-year-old worker?The regression's predicted earnings for a 25-year-old worker are $(Round your response to two decimal places.)Will the regression give reliable predictions for a 81-year-old worker?A. No, the oldest worker in the sample is 65 years old; 81 years is far outside the range of the sample data.OB. Yes, although the oldest worker in the sample data is 65 years old, the model is developed to make forecasts andpredictions for workers younger than 25 years of age and older than 65 years of age.Given what you know about the distribution of earnings, do you think it is plausible that the distribution of errors in the regression isnormal?O A. No, the distribution of earnings is negatively skewed and has kurtosis smaller than the normal.OB. Yes the distribution of earninas is symmetric and thus normalClick to select your answer(s).DELLsearch

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A regression of average weekly earnings (AWE, measured in dollars) on age (measured in years) using a random sample of college-educated full-time workers aged 25-65 yields the following: AWE = 647.9310 + 8.9280 x Age, R2 = 0.021, SER = 580.4. %3D The coefficient shows the marginal effect of Age on AWE; that is, AWE is expected to increase by $ for each additional y of age. is the intercept of the regression line. It determines the overall level of the line. (Round your responses to four decimal places.) The standard error of the regression (SER) is 580.4. What are the units of measurement for the SER? A. Dollars. O B. Dollars per year. O C. Unit-free. D. Dollars per week.

A regression of average weekly earnings (AWE, measured in dollars) on age (measured in years) using a random sample of college-educated full-time workers aged 25-65 yields the following: AWE = 647.9310 + 8.9280 x Age, R2 = 0.021, SER = 580.4. %3D The coefficient shows the marginal effect of Age on AWE; that is, AWE is expected to increase by $ for each additional y of age. is the intercept of the regression line. It determines the overall level of the line. (Round your responses to four decimal places.) The standard error of the regression (SER) is 580.4. What are the units of measurement for the SER? A. Dollars. O B. Dollars per year. O C. Unit-free. D. Dollars per week.

A First Course in Probability (10th Edition)

10th Edition

ISBN:9780134753119

Author:Sheldon Ross

Publisher:Sheldon Ross

Chapter1: Combinatorial Analysis

Section: Chapter Questions

Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...

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A regression of average monthly expenditure (AME, measured in euros) on average monthly income (AMI, measured in euros) using a random sample of college-educated full-time workers earnings €100 to €1.5 million yields the following: AME = 710.7 + 8.8 × AMI, R2 = 0.030, SER = 540.30 d. What does the regression predict will be the expenditure of a person with an income of €100? With an income of €200? e. Will the regression give reliable predictions for a person with an income of €2 million? Why or why not? ( f. Given what you know about the distribution of earnings, do you think it is plausible that the distribution of errors in the regression is normal? (Hint: Do you think that the distribution is symmetric or skewed? What is the smallest value of earnings, and is it consistent with a normal distribution?).
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3. A study of beer consumption using the annual data from 1980 -2001 produced the following regression: Y = 0.41 +0.052.X₁; −0.047X2; +0.032X3; −0.018X4i (0.027) (0.011) (0.009) (0.008) (0.009) R² = 0.94 F = 66.58 DW statistic=1.32, figures in the brackets are standard errors Where: Y₁ = Annual aggregate beer consumption in year t (billion pints) X₁₁ = Real disposable income income in year t ($ billions at 2001 prices) X2i = Price of beer in year t (index number with 2001 = 100) X31 Price of wine and sprits in year t (index number with 2001 = 100) = X4₁ = Price of cigarettes in year t (index number 2001 = 100) (a) What is the effect of a change in the price of beer on beer consumption? Does it have the correct sign? Explain. (b) Comment on the signs of the other three coefficients. Are they as expected? (c) Tests the significance of the coefficients on each of the variables Xit i = 1, 2, 3, 4. What assumptions have you made in carrying out these tests? (d) What conclusion do you draw…
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