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Using a random sample of 670 individuals for the population of people in the workforce in 1976, we want to estimate the impact of education on wages. Let wage denote hourly wage in 1976 U.S. dollars and let educ denote years of schooling. We obtain the following OLS regression line: wage = -0.54 + 0.54educ. How do you interpret the slope of this regression line? What is the expected difference in the hourly wage between a worker that finished four years of college and a worker with finished high school? What is the predicted wage for a person with one year of education? Does that make sense? If it is not, what is the name of this problem in econometrics? How do we deal with it?
Suppose you are interested in the effect of skipping classes on college GPA, and collect a sample of economic variables from 400 college students to analyze the problem. Included in your data are college GPA on a four-point scale (COLGPA), high school GPA on a four-point scale (HSGPA), achievement test score (ATS), and the average number of Economics 122B lectures missed per week (SKIP). Running a regression of the dependent variable COLGPA on the other explanatory variables including a constant (and homoskedastic errors) yields:
Identify the (time, censor) pair for each of the following analyses:
Statistics Can Lead to Errors The use of statistics can often lead to wrong conclusions or wrong estimates. For example, we may want to find out the average savings by i
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You are a business analyst working for a company called Combined Computers Pty Ltd. You have been asked to prepare a business report with statistics in it for the managing director
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The management at Superior Health Care System Incorporated recently purchased several new facilities including the central patient information management center. This purchase will
1. For each of the following variables: major, graduate GPA, and height: a. Determine whether the variable is categorical or numerical. b. If the variable is numerical, deter
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