mid term - Part I. [21 points] Multiple Choice: the...

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Part I. [21 points] Multiple Choice: the following questions has 0, 1, 2, 3 or 4 correct answers. Each question is worth 3points. Question 1 - The null and alternative hypothesis setting. Question 2 - The OLS estimator cannot be computed in this situation. Question 3-1 – Option C - is a random variable, it can take on many different values and so if it is ̂ centered around the true , we can have confidence that doing hypothesis testing regarding is valid. Question 3-2 – Option C - Minimizing the standard error estimates for . ̂ ̂ Question 3-3 – Option B - The part of the model that explains the predicted movement in the independent variable Question 3-4 – Option D – R square must greater than 0.2 Question 3-5 – Option C – 1.40 Part II. Please respond to every part of every question, and show your work where possible. Question 1 is worth 21 points, question 2 is worth 15 points, and question 3 is worth 24 points. 1) [21 points] Suppose we’ve collected a sample of 47 observations of hourly wages in US dollars ( HrWage ) and years of tenure ( Tenure ) at current sales related jobs in 2008. We wish to estimate the parameters of the following model: Using Ordinary Least Squares regression, we obtain the following results: s.e (1.242) (0.267) Number of Observations = 47 Mean HrWage = 12.885 Mean Tenure = 2.808 Sum of Squared Residuals = 2072.26 Total Sum of Squares = 2259.02 Explained Sum of Squares = 186.02 Given the information above, answer the following questions:
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a) [3 pts] Interpret, in full , the estimate for the coefficient of tenure above (yes, I know it’s the slope but what does is tell us)? The slope for HrWage is 0.538 says that for an increase in HrWage the tenure is increased by 0.538. [4 pts] Compute the variance of the regression, and Var ( ). ̂ The variance of the regression = Sum of Squared Residuals/n-2 = 2072.26/45 = 46.05022 c) [4 pts] Compute the R2 for this regression. In general, what does R2 tell us (interpret what this statistic tells us in words)? Coefficient of determination, R square = Explained sum of squares/ Total sum of squares = 186.02/2259.02 = 0.082345 The coefficient of determination, R square = 0.082345 this means that 8.23% of variation of Hr wages is influenced by Tenure. d) [5 pts] Is the estimated effect of years of tenure on the hourly wage of sales persons
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This note was uploaded on 12/04/2011 for the course ECONOMICS 201 taught by Professor Rcollier during the Spring '10 term at Portland CC.

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mid term - Part I. [21 points] Multiple Choice: the...

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