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Problem 3 Simple Bivariate Regression Consider the following bivariate regression model: NAMEUIN Page 1 of 2 = Hourly Wages, Bo+B₁Education; + & where Education measures the years of experience at the job for an individual and Hourly Wage is the hourly wage in dollars. The subscript i indexes various people. You run a bivariate OLS regression to estimate Bo and B₁. Suppose you estimate B = 10 and B a. 0 = 2 How do you interpret the estimates ßo and ß₁ in this context? (3 points) 1 b. Define the terms "predicted/fitted value" and "residual”. (3 points) c. Suppose that for some individual, the predicted value of Hourly Wage is $20, and the residual is 2. What is the actual Hourly wage for the individual? Show your work. (4 points) d. Suppose that some individual has 10 years of Education, and his actual hourly wage is $35. What is the predicted outcome and residual for this individual? Show your work. (5 points)

Problem 1 The Core Model Suppose you are interested in studying the effect of workers' training (measured by the number of training hours) on employee productivity (measured by output per hour). a. What is the dependent and independent variable in this setting? (2 points) b. How would you write this relationship using the Core Model? (3 points) C. Do you expect the slope coefficient ẞ₁, (which shows relation between teacher's experience and test scores) to be positive or negative? Explain your reasoning. (5 points) d. Name any two factors that are likely included in the error term of your model? (5 points)