ISM 5219 Test 1

You may work in groups of 1, 2, or 3 class members.

1. Consider linear regression. What is the difference between R square and adjusted R square? What does the intercept value mean? What does the x variable coefficient mean? What does R square mean? What does F significance mean?

2. Click on this link to download a workbook containing 5 samples of data. Y is the dependent variable. Prepare a scattergraph for each of the 5 samples. Put a linear trendline on each graph, showing the equation for the line and its r-square value. Perform a linear regression analysis for each of the 5 samples. Plot the residuals for each of the 5 regression models. Make a single table containing intercept, x variable coefficient, p values for the preceding two statistics, R square, adjusted R square, and F significance for each of the 5 regression models. Use the language of the textbook and/or of the following web page

http://www.stat.yale.edu/Courses/1997-98/101/anovareg.htm

to interpret all of the statistics in your table for each of the 5 regressions and to evaluate the 5 models.

3. For each of the 5 data samples of question 2, divide the data into two sets, with about the same number of points in each set. If the data is a time series, have an early half and a late half. Use one half (the early half for the time series data) as a "learning sample" and the other half as the "test sample". Fit a linear regression model to the learning sample. Evaluate your fitted model "in-sample". Then test the learned model on the second half of the data and evaluate the model "out-of-sample". Present your results in tabular form with a narrative explanation.

4. Download data for prime rate and CPI, at least 30 years of concurrent monthly data for each. Divide this data into 2 approximately equal intervals. Calculate change in each series for 3 month intervals. Fit an autoregressive model to change in the earlier interval for each time series. Test that model on each of the out-of-sample intervals. Evaluate the models in-sample and out-of-sample. Present your results in tabular form with a narrative explanation.

5. For the intervals of prime rate and CPI data of question 4, fit a model in which change in prime rate is the dependent variable and some lagged period change in prime rate is one independent variable and some lagged period change in CPI is the other independent variable. Fit your model in-sample, on the earlier interval, and evaluate it in-sample, on the earlier interval,  and out-of-sample, on the later interval. Present your results in tabular form with a narrative explanation.

6. For the intervals of prime rate and CPI data of question 4, fit a model in which change in CPI is the dependent variable and some lagged period change in CPI is one independent variable and some lagged period change in prime rate is the other independent variable. Fit your model in-sample, on the earlier interval, and evaluate it in-sample, on the earlier interval,  and out-of-sample, on the later interval. Present your results in tabular form with a narrative explanation.

Put all of this work into a .DOC file and attach it to an email with the subject "ism 5219 test 1 your name" and send the email to william.leigh@bus.ucf.edu by 10 pm on the night of the test (6/16/2005). If there are multiple members of your group have as the subject "ism 5219 test 1 group", and list the group member names in the body of the email.

Thank you.