Maximum Likelihood Estimation

Kuber Deokar

Aim of Course:

Maximum likelihood is a popular method of estimating population parameters from a sample. This course will cover the derivation of maximum likelihood estimates, and their properties. After successfully completing this course, you will be able to derive maximum likelihood estimates, interpret them, and be able to assess both the advantages and disadvantages of using a maximum likelihood estimate in a particular situation.

Who Should Take This Course:

Maximum likelihood estimation is used in many of the methods taught in statistics.com's intermediate and advanced courses(Survival Analysis, Logistic Regression and Generalized Linear Models, to name a few). Students who need to understand the theory behind those methods should take this course first.

Course Program:

The course is structured as follows

The Instructor:

Kuber Deokar holds a Masters degree in Statistics from Pune University, India, where he also taught undergraduate statistics. Mr. Deokar holds the position of Instructional Operations Supervisor at statistics.com. He is responsible for coordination of statistics.com online courses, and ensures seamless interactions between the management team, course instructors, teaching assistants and students. He also serves as the senior teaching assistant and shares instructional responsibilities for several courses, and handles consultancy assignments, working from in our office in Pune, India.

Organization of the Course:

This is a special stastistics.com course that consists of self-study materials. The course was designed by Dr. Thomas P. Ryan and your instructor for this session will be responsible primarily for reviewing and answering questions regarding homework assignments.

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 where you can post questions about the homework. The course is scheduled to take place over 2 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 Program in Advanced Statistical Studies 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), 2.50 CEU's and a certificate will be issued by statistics.com, upon request.

Dates:

Dec. 18, 2009 - Jan. 1, 2010
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 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:

The equivalent of Introduction to Statistics 1: Inference for a Single Variable, and Introduction to Statistics 2: Working with Bivariate Data (and, if necessary before these courses, Introduction to Statistics for Beginners or Survey of Statistics for Beginners).

Course Text:

All course readings will be supplied to students.

Software:

No specific software is required. Access to one or more of these software packages- SAS, R, S-plus, Stata, Minitab, StatXact, LISREL, will enhance your experience with this course.

Registration:

Register Online - $199
Register Online (academic) - $169 (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.