Economics 3972
Fall 2003
Instructor: Noel Brodsky
 Office: 2831 (215D) Coleman Hall
Phone: 581-6334
 Hours: 1:00pm-2:00pm MWF
or by Appointment

2 REGULAR EXAMS (250 POINTS EACH)                                 = 500 POINTS
1 FINAL EXAM (CUMULATIVE)                                                = 350 POINTS
                                                                                        TOTAL     1000 POINTS

Expected Grade Distribution and Curve Structure:
Curve Structure: Average exam score will be set at or near a baseline "B", excluding all zeros, whenever necessary. Each exam has its own curve, absolutely determined one week after the exam is returned.

The Cutoffs are as follows:

88% = A, 77% = B, 66% = C, 55% = D, below 55% is an F

Special Information: Term papers: Both papers must utilize a word processor, done by the student turning the paper in for his or her grade. Failure to do this will result in a failing grade for the paper. The second paper is absolutely required for the course, and regardless as to the point value of the paper, failure to turn it in will result in an automatically failing grade for the course.  The first paper will be a short (5-7 pages) exposition of statistical data and a regression that is given to you. The second paper is of your own making, subject to my approval. A poor topic choice is serious, and can result in a loss of 3 (three) letter grades on the final paper. It is a longer paper, say about 10-15 pages. Do not ever copy from someone else.

Important Dates: First Paper due: November 17, 2003 at 4:00pm Paper Length: 5-7 pages, word processed, double spaced, your work. The paper may be turned in on Wednesday, November 19, 2003, with the loss of 2 letter grades, each day thereafter, one letter grade is lost.

Second Paper: Proposal Due November 21, 2003 Paper Length: 10-15 pages, word processed, double-spaced, your work.  Final Draft Due Wednesday December 10, 2003, at 4:00pm. The paper may be turned in on Friday December 12, 2003, with the loss of 2 letter grades, each day thereafter, one letter grade is lost.

Exams: Generally, expect an exam to come at the end of Simple Linear Regression, and another at the end of Multiple Regression. Students have one week to challenge an exam grade, after this the exam is closed, and a final curve for that exam is given. Make-Up Exams: There must be a very compelling reason to be granted a make-up exam, which, if at all possible, should be arranged in advance. I do not intend to give make-up exams, if I can avoid it.  If you have a documented disability, and wish to discuss academic accommodations, please contact me as soon as possible.

Special requirement: All students are required to have a computer account. You will be given assignments that require you to find data on the Internet, and report to me via email. These assignments are required, and carry no point value. Required means that the assignments must be completed to receive a grade for the course. The assignments will be announced in class. Please note that this course is designated writing intensive. This means that part of your grade is a result of your writing style. The final paper can be submitted to the electronic writing portfolio required for graduation from Eastern.

 - N. Brodsky, Instructor

Text: Statistics for Economics and Business, 5th ed. Newbold, Carlson and Thorne, Prentice Hall, Upper Saddle River, NJ, 2002

Chapter Topic Assignment
9-9.7, 9.8,9.9 Review: Hypothesis Testing, Confidence Intervals            9.8,9,13,48,51,58,68,77
Tests on means (Z&t), variances (2), F-test.                     
10.1 Correlation Analysis                                                                      10.2,4,6,7
10.2 Linear Regression Model                                                              10.12,14,15
10.3 Least Squares Coefficient Estimators
10.4 The Explanatory Power of a Linear Regression Equation
10.5 Statistical Inference: Hypothesis Tests and Confidence Intervals     10.19,21,24 ,40
10.6 Prediction                                                                                     10.34, 44
10.7 Graphical Analysis


11.1 The Multiple Regression Model                                                     11.1, 2, 3
11.2 Estimation of Coefficients
11.3 Explanatory Power of a Multiple Regression Equation
11.4 Confidence Intervals and Hypothesis Tests for Individual Regression Coefficients     11.18, 20, 21, 22
11.5 Tests on Sets of Regression Parameters                                        11.23, 26, 27
11.6 Prediction                                     
11.7 Transformation for Nonlinear Regression Models                          11.41, 42, 43
11.8 Dummy Variables for Regression Models                                     11.48, 49, 50, 53
11.9 Multiple Regression Analysis Application Procedure                     11.57, 58, 59, 70, 77
12.1 Model-Building Methodology                            
12.2 Dummy Variables and Experimental Design                                  12.4
12.3 Lagged Values of the Dependent Variables as Regressors            12.5
12.4 Specification Bias                                                                        12.15
12.5 Multicollinearity                                                                           12.18, 19, 40
12.6 Heteroscedasticity                                                                       12.20, 21, 45
12.7 Autocorrelated Errors                                                                  12.23, 30, 41, 42


17.3 Components of a Time Series
17.4 Moving Averages
17.5 Exponential Smoothing                                                                17.33, 34
17.6 Autoregressive Models                                                                17.37, 38
14.1 Goodness of Fit Tests: Specified Probabilities                              14.1, 14.3
14.2 Goodness of Fit Tests: Population Parameters Unknown              14.11, 16
14.3 Contingency Tables                                                                     14.18, 19, 32

FINAL EXAM (cumulative)