Course Prerequisite: AMS 102, AMS 310, or equivalent.

Course Objectives:

1. To learn the new statistical techniques of multiple regression and analysis of variance.
2. To learn how to use statistical packages to perform computations and to interpret the results.
3. To apply these techniques in an A versus B comparison study.
4. To apply multiple regression techniques to a synthetic data set.

Course Text: Norusis, Marija J. SPSS: SPSS 8.0 Guide to Data Analysis. Upper Saddle River, N.J.: Prentice Hall.

Course Instructor and Office Hours

Professor Finch, Math Tower, 1-112, phone: 632-8369, Tuesday and Thursday from 1:00 to 2:00, and Thursday from 4 until 5 or by appointment. My e-mail is FINCHS@ccvm.sunysb.edu. I will be available after class to make appointments or have short discussions.

The book has 23 chapters, and we will cover all except Chapter 17. There are 28 classes, with six reserved for examinations, reviews, and returning papers. The pace of the class is roughly one chapter per lecture, but I will go through the earlier review chapters somewhat faster. The tentative schedule is:

Sept. 3: Introduction to the course and Chapter One

Sept. 7: Chapters Two and Three

Sept. 9: Chapter Four

Sept. 14: Chapters Five and Six

Sept. 16: Chapter Nine (I will postpone the discussion of contingency table techniques)

Sept. 21: Chapter Ten

Sept. 23: Chapter Eleven

Sept. 28: Chapter Twelve

Sept. 28: Proposal on A versus B Comparison Due

Sept. 30: Chapter Thirteen, Proposal returned

Oct. 5: Cushion and review.

Oct. 7: Examination One, Chapters 1-6 and 9-13.

Oct. 12: Examination One returned, discussion

Oct. 14: Chapter Seven

Oct. 19: Chapter Sixteen

Oct. 21: Chapter Eighteen

Oct. 26: Chapter Eight and Nineteen

Multiple regression project dataset distributed

Oct. 28: Chapter Twenty

Nov. 2: Chapter Twenty One

Nov. 2: Report on A versus B Comparison Due

Nov. 4: Chapter Twenty Two

Nov. 9: Supplemental discussion of Time Series

Nov. 11: Chapter Twenty Three

Nov. 16: Cushion and review

Nov. 18: Examination 2, Chapters 1-13, 16, and 18-23

Nov. 23: Examination returned and discussed.

Nov. 25: Thanksgiving

Nov. 30: Chapter Fourteen

Dec. 2: Chapter Fifteen

Dec. 7: Experimental Design in Six-Sigma

Dec. 9: Course Summary

Thursday, Dec. 16, Final Examination: 3:30-6:30.

My expectation is that you will review the chapter that we are going to be discussing in class before you come to class and that you will read the chapter and course material on the web carefully after class. Course material will include problems to work on. Also you should review the material from your prerequisite course as we go through the material in this course.

Examination Requirements

There will be three examinations, two in-class examinations and a final. Each examination is comprehensive. Example problems for examinations will be made available on the class web site. You may use your text and an approved calculator in the examination provided that you permit the proctor to inspect them during the examination. You may also use notes, but these notes must be stapled or taped to the text. Any loose papers will be confiscated. Any tables and graphs that are not in your text but needed to solve problems will be provided. You may not use any other assistance during the examination. Since this course covers material examined in the professional sequence of the actuarial society and is part of standard curriculums developing expertise in financial issues, I will strictly enforce academic dishonesty rules.

The examination component of your grade, E, will be calculated by the rule E₁+E₂+E_F. Each problem task will be worth ten points and will require a numerical answer. The total point value of the examinations will be approximately 1100 points.

A second component will be your data analysis projects. A one page paper specifying the project, the data that will be used, and the objective of the analysis is due on September 28. I will return this with comments on September 10. The paper will be due on November 2. This project will be worth a maximum of 400 points. I will distribute a multiple regression data set for you to analyze on October 26. Your report on your data set is due on December 9. It will be worth 600 points. The sum of the two scores is P and is added to your exam score.

There will be six homework assignments. Each will be graded on an acceptable or unacceptable basis. Each acceptable assignment will earn 50 points. Additionally, students who score less than 100 points on an in-class examination can submit a solution to an alternate form to get an additional 25 points. The sum of these scores is H, and it is added to your score.

Finally, you are encouraged to define additional projects that can be used for extra credit. This can include expanding your A versus B comparison project, working additional problem sets to strengthen your skills, and writing reports of readings on statistically related issues. Do not start such extra credit projects without discussing them with me and the point value of the task. The total value of these efforts is called X and is added in.

That is, I will sum the four components (E, P, H, and X). In general, I will assign grades according to this ranking. A major exception is that a student who has both a strong A final and a strong A multiple regression project will receive an A in the course. Similarly, a student with both a strong B in the final and a strong B in the multiple regression course will receive at least a B in the course. The principle is that I am more interested in how strong you were at the end of the course than I am in how troubled your start in the course may have been.

The use of the computer in this course is essential. The course text and lectures will focus on SPSS. There are many other packages that are available. In particular, SAS is widely used in industry. Spreadsheets perform many of the computations covered in this course but are limited with regard to multiple regression diagnostics. You are free to use the statistical program of your choice. Using a program other than SPSS may limit the extent of assistance that the TA and I can give you.

Students with Disabilities

The following statement is inserted in this syllabus as part of official University policy:

"If you have a physical, psychiatric/emotional, medical or learning disability that may impact on your ability to carry out assigned course work, I would urge that you contact the staff in the Disabled Student Services office (DSS), Room 133 Humanities, 632-6748/TDD. DSS will review your concerns and determine, with you, what accommodations are necessary and appropriate. All information and documentation of disability is confidential."

I will follow DSS recommendations with regard to any student's situation.