Introduction to Resampling Methods

taught by Peter Bruce

Brief Description:

The course introduces the basic concepts and methods of resampling methods, including bootstrap procedures and permutation (randomization) tests, with little or no complex theory or confusing notation.

Instructor(s):
Level: Introductory/intermediate

Who Should Take This Course:

Analysts with data or statistics not suitable for standard analysis (small sample sizes, for example, or non-standard statistics), analysts who have had some statistics and want to deepen their knowledge of statistical inference, statisticians unfamiliar with resampling seeking a basic introduction, instructors interested in the easy-to-understand, non-formula-based resampling approach.

Dates:
July 06, 2012 to July 27, 2012
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Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

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Introduction to Resampling Methods

taught by Peter Bruce

Aim of Course:

The course introduces the basic concepts and methods of resampling methods, including bootstrap procedures and permutation (randomization) tests. The approach of the course is to teach inference: interval estimation, one- , two- and k-sample comparisons, correlation, regression, from a resampling perspective, without complex theory, mathematics or confusing statistical notation. A companion course, Bootstrap Methods, covers the bootstrap with more theory and in greater detail.

See:  Bootstrap Methods

Prerequisite(s):

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

Course Program:

SESSION 1: The Resampling Approach to Inference

• Historical perspective
• Hypothesis tests vrs. confidence intervals
• Permutation tests
• The bootstrap
• Virtues of a "naive" do-it-yourself approach
• The 4-step process
  • Specify population(s)
  • Specify resampling procedure
  • Calculate statistic or estimate of interest
  • Repeat and keep score
• Working with measured data

SESSION 2: Working with Count Data

• The contingency table
• Choice of test statistics
• Fisher's Exact Test
• Chi-Square Test
• Dose-Response Relationship

SESSION 3: Working with Multivariate Data

• ANOVA
• Correlation
• Regression

HOMEWORK:

Homework in this course consists of short answer questions to test concepts and guided data analysis problems using software.

Organization of the Course:

This course takes place over the internet at the Institute for 3 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, 3.75 CEU's and a record of course completion will be issued by The Institute, upon request.

Course Text:

The required text for this course is Resampling: The New Statistics by Julian Simon, available online here.

Software:

Course exercises will be provided in Resampling Stats for Excel and, in some cases, in R. Teaching Assistants can offer limited assistance with R in this course. Click Here for information on obtaining a free (or nominal cost) copy of various software packages for use during the course.

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Introduction to Resampling Methods

taught by Peter Bruce

Instructor(s):
Dates:
July 06, 2012 to July 27, 2012
Course Fee: $399
Academic Rate: $299

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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