Nonparametric Statistics

Brief Description:

This course teaches you how to perform a range of nonparametric statistical analyses - robust procedures that do not assume that data are samples from prespecified families of distribution such as the normal or exponential.

Instructor(s):
Level: Intermediate

Who Should Take This Course:

Researchers in the physical, life or social sciences, pharmacology, medicine, management, market research, who deal with data that do not conform to assumptions such as normality needed for validity of standard parametric procedures; in particular, those analysts who must publish the results of studies where parametric procedures may be inappropriate, and not accepted by regulators or referees.

Dates:
To be scheduled.
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

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Nonparametric Statistics

Aim of Course:

This introduction to nonparametric methods teaches you how to perform a range of statistical analyses that do not assume that data are samples from pre-specified families of distribution such as the normal or exponential. Course participants will learn how to implement a variety of rank based and other test and estimation procedures for univariate data from observational studies or designed experiments, also methods for correlation and linear regression for bivariate data. More advanced procedures including smoothing techniques for large data sets will also be introduced.

Prerequisite(s):

If you are unclear as to whether you have mastered the requirements, try these placement tests here.

Course Program:

In each session, some of these topics will be designated as core topics for all participants. Other will be optional and participants may select from these any topics of special interest to them when time permits. They may also return to such optional topics after the course is completed if there is not time available during the course.

SESSION 1:

• What are nonparametric methods?
• When should they be used?
• Permutation and randomization tests
• Some classic rank or order based tests for location differences
  • Wilcoxon signed-rank test
  • The sign test
  • Wilcoxon-Mann-Whitney test
  • Kruskal-Wallis test

SESSION 2:

• Further rank or order based tests
  • Jonckheere-Terpstra test
  • Friedman-Rank sum test
• Procedures for bivariate data
  • Spearman and Kendall correlation coefficients
  • Theil-Kendall and related methods for linear regression
• Goodness of fit tests for samples from continuous distributions

SESSION 3

• Nonparametric analyses of factorial treatment structures
• Specific and multiple comparison tests
• Analysis of survival data

SESSION 4

• Robustness
• The bootstrap
• Count data
  • Categorical data
  • Measures of association
• Modern nonparametric procedures

Organization of the Course:

This course takes place over the internet at the Institute for 4 weeks. 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 typically requires 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, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Credit:
Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:

1. You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
2. You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
3. You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course, 5.0 CEU's and a record of course completion will be issued by The Institute, upon request.

Course Text:

Applied Nonparametric Statistical Methods, Fourth Edition by Peter Sprent and Nigel C. Smeeton, from Chapman & Hall/CRC Press. This text can be ordered directly from CRC press using this form. CRC Press usually gives a 25% discount when the book is ordered using the above form. Please be sure you obtain your copy before the start of the course - this is a "print on demand" text, so it takes approximately 7 days to receive from the publisher. Note also that earlier editions of the book are not suitable for the course.

Software:

The main software used in the course is StatXact. A few procedures introduced in the course are not covered by StatXact but are included in the standard statistical package that you would have used in your introductory statistics course. (Note: R has programs for nearly all the procedures in the course, but it requires a lot of practice to make best use of its facilities so at the level of this course it is not recommended for anyone who is not already familiar with it.) Click Here for information on obtaining a free (or nominal cost) copy of software for use during the course.

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Nonparametric Statistics

Instructor(s):
Dates:
To be scheduled.
Course Fee: $499
Academic Rate: $399

Before registering, please read the syllabus tab, noting the prerequisites, text and software requirements. When you click the register button, you will be taken to our secure transaction page.

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