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Unformatted text preview: Econ*2740, Winter 2011: Written Empirical Assignment Due Tuesday 5th April Final Version About the Data Each student has a data file containing values on 5 variables: ‐ the price at which a house was sold ‐ the size of the house in square feet ‐ the lot size in square feet ‐ the presence/absence of a fireplace ‐ the age of the house in years Each dataset is taken from Multiple Listing Service data from the city of Guelph for a 12 month period in the early 1980s. Additional information will be provided online. The first step is to open Excel and open the data file. The Excel wizard will guide you through the steps: note that your data are “delimited” using “commas.” At the final stage you should find that the data have been parsed (separated) into 5 columns. You may choose to label the columns by inserting a row. The columns are in this order: Price, Size, Lot Size, Fire Place, Age. Grading: Each task will be graded out of 20 points for a total 120 points. In addition, you should write an introduction that will be graded out of 10 points. The total points available is therefore 130 points. Task 1 Compute and report summary statistics for all five variables. Interpret the table of summary statistics (interpret the statistical measures and their units of measure) Task 2 Create histograms of (a) price (b) size. Select and appropriate number of bins/cells for each histogram and label the charts appropriately. Task 3 Compute correlation coefficients for all 5 variables (report, interpret and discuss selected values). Create, report and discuss a scatter plot of price and size. Task 4 Construct a 90% confidence interval for the population mean lot size. Construct a 95% confidence interval for the population proportion of houses with fireplaces. Explain your methods. Task 5 Test the hypotheses that the population means of price, size, lot size and age are identical for houses with and without fire places (4 hypothesis tests). Justify your assumptions concerning the population variances. Task 6 Compute a simple regression in which price is the dependent variable and size is the explanatory variable (also include an intercept). Interpret the regression coefficient on size, its standard error and its t‐statistic. Interpret R‐squared. Paste the regression results into your report. ...
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This note was uploaded on 02/02/2012 for the course ECON 2410 taught by Professor Prescott during the Fall '11 term at University of Guelph.
- Fall '11