Tutorial 5 20-01-10

Tutorial 5 20-01-10 - Tutorial5ComputerWorkshop...

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Tutorial 5  – Computer Workshop  Wednesday 20 th  January, 2010 ECMT 1020 - Business and Economic Statistics B Aim: To extend the students from simple regression to multiple regression. To enable students to estimate a multiple regression model in EXCEL and interpret the output. Instructions: 1. Complete the "Learning the Concepts" questions BEFORE attending your workshop. (The questions will be reviewed in class) 2. The "Applying the Concepts" the questions will be done in workshop. 3. Complete the "Review Questions" after attending your workshop. These questions are in multiple choice format and are posted on blackboard. Learning the Concepts Question One (1.1) y i = β 0 + β 1 X 1i + β 2 X 2i + β 3 X 3i + ε ι (1.2) i i i i x x x y 3 2 1 02 . 3 98 . 0 48 . 2 89 . 1 + - + = A. From the equations 1.1 and 1.2 above, identify the following: a) Explanatory variables b) Error term c) Coefficients d) Dependent variable e) Estimated coefficients f) Fitted value or predicted value g) Intercept B. Which of the terms above measures the estimated marginal effect of x 2 on y ? If we assume that all units are in dollars, give the full interpretation of this marginal effect.
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C. Write out the estimated linear regression equation with the dependent variable , instead of the fitted value. What changes? Question Two (2.1) i i i i i u x x x y + + - + = 3 2 1 52 . 1 44 . 2 99 . 1 95 . 3 Which of the following statements is true? (a) For a 1.99 increase in the variable x 1 , y will increase 1 unit on average, holding all other x variables constant. (b) For a 1 unit increase in the variable x 2 , y will decrease 2.44 units on average. (c) For a 1unit increase in the variables x 3 , y will increase 1.52 units, holding all other x variables constant. (d) None of the above. If you answered (d), what would a correct interpretation of the marginal effect, or estimated slope coefficient, be for a linear multiple regression such as equation (2.1) ? Question Three (3.1) y i = β 0 + β 1 x 1i + β 2 x 2i + β 3 x 3i + ε ι (3.2) y i = 2.5 + 1.5 x 1i 1.0 x 2i + e ι a) From the two equations above, identify the true linear multiple regression model and the estimated linear regression model. b) What feature do you notice about the explanatory variables of the estimated regression model when compared to the true model? Given this, how much confidence do you have in the estimated coefficient values? Why? What about for the model (3.3) below? (3.3) i i i i i i u x x x x y + + + - + = 4 3 2 2 1 2 . 1 3 . 2 7 . 1 9 . 1 8 . 2
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Applying the Concepts Question Four: Group Exercise Part A: Importing the Data into Excel: Open the data file: hprice.xls from Blackboard Workshops/ Data Check you have a file of 12 variables, and 546 observations (plus 1 row of data labels). Part B: Specifying Your Linear Model:
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This note was uploaded on 11/02/2010 for the course ECMT 1020 taught by Professor Bo during the Three '10 term at University of Sydney.

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Tutorial 5 20-01-10 - Tutorial5ComputerWorkshop...

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