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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:
Two students are sitting in a lecture and considering whether to ask a question from the professor (both of them are considering the same question). If they both ask, the questi
We are interested in assessing the effects of temperature (low, medium, and high) and technical configuration on the amount of waste output for a manufacturing plant. Suppose that
You are interested in testing the distance of two golf balls, Brand A and Brand B. You take a random sample of 100 golfers, each of whom hits Brand A once and Brand B once. Define
how can i calculate seasonal index?
The mean tax-return preparation fee H&R Block charged retail customers in 2012 was $183 (The Wall Street Journal, March 7, 2012). Use this price as the population mean and assume t
In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o
The interest rate on the three year loan is 0.087. Whereas the interest rate on the two year loan is 0.085 as given in A. Suppose that the liquidity premium at t=1 is 0.002 and tha
Mean Absolute Deviation To avoid the problem of positive and negative deviations canceling out each other, we can use the Mean Absolute Deviation which is given by
Coefficient of Determination The coefficient of determination is given by r 2 i.e., the square of the correlation coefficient. It explains to what extent the variation
The following dataset is from a study of the effects of second hand smoking in Baltimore, MD, and Washington, DC. For the 25 children involved in this study the outcome variable is
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