Regression Analysis

Dr. Samprit Chatterjee

Aim of Course:

Regression, perhaps the most widely used statistical technique, estimates relationships between independent (explanatory) variables and a dependent (outcome) variable. Regression models can be used to help understand and explain relationships among variables; they can also be used to predict actual outcomes. In this course you will learn how linear regression models are derived, use software to implement them, learn what assumptions underlie the standard regression model, learn how to test whether your data meet those standard assumptions, and learn what can be done when those assumptions are not met.

Who Should Take This Course:

Scientists, business analysts, engineers and researchers who need to model linear relationships in data. If you were introduced to regression in an introductory statistics course and now find you need a more solid grounding in the subject, this course is for you. If you are planning to learn additional topics in statistics (for example, the data mining and forecasting courses at statistics.com), a good knowledge of regression is often essential.

For those enrolled in Professional Advancement Programs, this is a required or elective course in the following Programs:

• Statistics in Business & Marketing - required
• Data Mining - required
• Statistics for Social Sciences - required
• Statistics for Environmental Science - required
• Engineering Statistics - required

Course Program:

The course is structured as follows

The Instructor:

The instructor is Dr. Samprit Chatterjee, Professor of Health Policy at Mount Sinai School of Medicine, and Professor Emeritus of Statistics at New York University. He is a co-author of Regression Analysis by Example (the course text). He has also co-authored Sensitivity Analysis in Linear Regression and A Casebook for a First Course in Statistics and Data Analysis (both Wiley). Prof. Chatterjee has been a visiting professor at Stanford University, MIT's Sloan School of Management, Harvard School of Public Health, the Swiss Federal Institute of Technology (ETH) in Zurich, the University of Tampere and the University of Auckland (NZ).

Organization of the Course:

The course takes place over the internet, at statistics.com. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor. The course is scheduled to take place over 4 weeks, and typically requires 10-15 hours per week. At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.

Certificates and Grades:

You may be interested only in learning the material presented, and not be concerned with grades or certificates. Or you may be enrolled in a statistics.com Professional Advancement Program that requires demonstration of proficiency in the subject, in which case your work will be assessed for purposes of issuing a grade. Or you may require only a "Certificate of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's). As you begin the class, you will be asked to specify your category.

Credit:

This course offers continuing education units (CEU's). For those successfully completing the course (generally this means marks of 50% or better on the homework), 5.0 CEU's and a certificate will be issued by statistics.com, upon request.

Dates:

Oct. 3 - Oct. 31, 2008
Click here to be notified of future course offerings.

Participants gain access to the online materials on the first day of the course, and typically spend about 10-15 hours per week (at their convenience). You retain full access to course materials, including discussion board, for two weeks after the course closing date.

Level:

Intermediate

Prerequisite:

You should have the equivalent of an introductory course in statistics such as Basic Concepts in Probability and Statistics, Introduction to Statistics 1: Inference for a Single Variable, and Introduction to Statistics 2: Working with Bivariate Data including a basic understanding of the concepts of statistical inference (confidence intervals and hypothesis tests). The math level is basic algebra. The additional preparation found in Introduction to Statistics 3: Regression and ANOVA is also helpful. For additional information about course prerequisites, click here.

Course Text:

The required text is Regression Analysis by Example, 4th Edition (be sure you get the 4th ed.). The previous link allows you to order the text directly from Wiley. Wiley typically offers a 15% discount to statistics.com customers during checkout time.

Software:

Students must also have access to and some familiarity with regression software. This familiarity is provided in statistics.com's introductory courses (Intro 1 and 2, see "Prerequisites" above), and also in the Introduction to R: Statistical Analysis. Please click Here for information on obtaining a free (or nominal cost) copy of statistical software packages that can be used during the course. All of the "General Purpose" software packages listed there will do regression. There will be some supplementary materials in the course to provide assistance with Minitab and Data Desk.

Registration:

Register Online - $449
Register Online (academic) - $349 (you must be affiliated with a college, university or high school)

Add $50 service fee if you require a prior invoice, or if you need to submit a purchase order or voucher, pay by wire transfer or EFT, or refund and reprocess a prior payment. Please use this printed registration form, for these and other special orders.

Note: Courses may fill up at any time and registrations are processed in the order in which they are received. Your registration will be confirmed for the first available course date, unless you specify otherwise.