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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:
An approximation to the error of a Riemannian sum: where V g (a; b) is the total variation of g on [a, b] dened by the sup over all partitions on [a, b], including (a; b
(a) Elevation (m) 0 400 800 1200 1600 2000 2400 2800 3200 4000 480
Bill Clinton reportedly was paid $10 million to write his book My Way. The book took three years to write. In the time he spent writing, Clinton could have been paid to make speech
How do you change the base of the index
Calculation for Discrete Series or Ungrouped Data The formula for computing mean is = where, f = fr
implications of multicollinearity
A real estate agency collected the data shown below, where y = sales price of a house (in thousands of dollars) x 1 = home size (in hundreds of square f
slope parameter of 1.4 and scale parameter of 550.calculate Reliability, MTTF, Variance, Design life for R of 95%
How can we analyse data with four bilateral response variables measured with errors and three covariated measured without errors?
The box plot displays the diversity of data for the totexp; the data ranges from 30 being the minimum value and 390 being the maximum value. The box plot is positively skewed at 1.
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