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   Courses> Applying Resampling Methods
 

Applications of the Bootstrap, Decision Trees, and Permutation Methods 

Begins June 19th 2015

Aim of the Course: This 3-week course will introduce you to the resampling methods--the bootstrap, CART, and the permutation test and then show you how to apply them in your work with practical examples from the medical device and pharmaceutical industries including how to obtain estimates of required sample size from empirical distributions and the analysis of contingency tables and cross-over designs.

Who Should Take This Course: Anyone who wants to make more effective use of  statistics in their work in the pharmaceutical and medical device industries.  An existing undergraduate background in estimation and testing hypotheses is essential.

Instructor: Dr. Phillip Good, former Calloway Professor of Computer Science at the University of Georgia (Fort Valley) and graduate of the program in mathematical statistics at U.C. Berkeley, is the author of Practitioner's Guide to Resampling Methods, (CRC, 2011), A-Z of Error-Free Research (CRC, 2012), Manager's Guide to Design and Conduct of Clinical Trials (Wiley, 2nd ed 2006), Resampling Methods (Birkhauser, 3rd ed, 2005), Introduction to Statistics via Resampling Methods and Excel (Wiley, 2005), Common Errors in Statistics (and How to Avoid Them) (Wiley, 4th ed 2012) with James Hardin), Permutation, Parametric, and Bootstrap Tests of Hypotheses (Springer, 3rd ed, 2004), and Applying Statistics in the Courtroom (CRC, 2001). He has given tutorials at the Joint Statistical Meetings (U.S.) and Deming Conference, lectured in Australia, Belgium, Bulgaria, France, Holland, Ireland, Slovenia, and Spain, and was a traveling lecturer for the American Statistical Association. This is his seventh (7th) year of providing on-line interactive courses. 

Prerequisite: You should have familiarity with basic statistical concepts.  If not, we highly recommend Introduction to Statistics via Resampling Methods and R (2nd ed, Wiley, 2013). Prior use of R, S-Plus or Stata is helpful.  Regretfully, few of these routines are available in SAS.

Organization of the Course: The course takes place over the Internet.  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 an alias and access to a private bulletin board that serves as a forum for discussion of ideas, problem solving, and interaction with the instructor. The course is scheduled to take place over three weeks, and should require about 10 hours per week. At the beginning of each week, participants receive the relevant material, in addition to answers to exercises from the previous session. During the week, participants are expected to go over the course materials and work through exercises. Discussion among participants is encouraged. The instructor will provide answers and comments.

Course Requirements: The optional text is Resampling Methods (Birkhauser, 3rd ed, 2005) by Dr. Good. The previous link allows you to order the text directly from Birkhauser. Birkhauser typically offers a 15% discount to statcourse.com customers during checkout time. If you'd prefer an electronic textbook, you may download the hyper-linked Practitioner's Guide. PLEASE ORDER YOUR COPY IN TIME FOR THE COURSE STARTING DATE. During the course, we will download from cytel.com and make use of a trial copy of StatXact for analyzing contingency tables.

Course Program: The course is structured as follows

SESSION 1: The Bootstrap

  • Which Statistic should we use?

  • Precision of an Estimate

    • Using the Bootstrap

  • Interval Estimates 

    • Improved Bootstrap Estimates

  • Estimating Bias

  • Better Bootstraps

SESSION 2:  Permutation Tests

  • Practical Applications

  • Comparing Means

  • Multivariate Data

  • Behrens-Fisher Problem

  • Comparing Variances

SESSION 3: Applying the Concepts

  • One-Way Analysis

  • Randomized Blocks

  • Contingency Tables

  • Model Validation

  • Classification and Regression Trees

  • Which Method should we use?

Cost: The full cost of this three-week interactive on-line course is only $229. Students, faculty and research workers at academic institutions are eligible for a further discount. Just send an email from your academic email account to courses@statcourse.com to receive a discount coupon worth $35 toward the cost of the course.

Immediately after your payment is credited, you will receive an email giving you a password, sign up instructions, and the web address (URL) of the course material. Note that you will not be able to access this address until the start date of the course.

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Refund Policy: Up until one-week prior to the start of a course, a refund of the fee paid less $35 will be provided on request.  Although there are no refunds after that date, course participants may re-enroll without charge the next time the course is offered.

 
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