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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:
The Maju Supermarket stocks Munchies Cereal. Demand for Munchies is 4,000 boxes per year and the super market is open throughout the year. Each box costs $4 and it costs the store
Measurement of trend , least square method
data:59,59,65,70,74 176,179,195,210,200
slope parameter of 1.4 and scale parameter of 550.calculate Reliability, MTTF, Variance, Design life for R of 95%
Suppose that before the minimum wage law change, the underlying mean number of part-time employees per Burger King Restaurant in New Jersey was 20.3. It was thought that the increa
Having 11 numbered balls -0 to 10 -into a basket and have 6 spaces to be numbered with the balls selected in each 6 chances and it returned it back to the basket each time. Chanc
how detect sources of error in sample survey
Type of Correlation 1. Positive and Negative Correlation: 2. Simple Partial and Multiple Correlations. 3. Linear and Non linear or Correlations
Consider three stocks A, B and C costing $100 each. The annual returns on the three stocks have mean $5 and variance $10. a. Suppose that the returns on the three stocks are i.i
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