ECONOMIC STATISTICS II
Economics 3972
Fall 2003
Instructor: Noel Brodsky
Office: 2831 (215D) Coleman Hall
Phone: 581-6334
Hours: 1:00pm-2:00pm MWF
or by Appointment
http://www.eiu.edu/~econinfo
GRADE DETERMINATION:
2 REGULAR EXAMS (250 POINTS EACH)
= 500 POINTS
2 TERM PAPERS (WORD PROCESSED-100&50 POINTS)
= 150 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.
ECONOMIC STATISTICS II ECN 3972
- N. Brodsky, Instructor
Syllabus
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
EXAM I
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
EXAM II
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)