Bootstrap Methods

taught by Michael Chernick
and Robert LaBudde

Brief Description:

This course covers the basic theory and application of the bootstrap family of procedures, with the emphasis on applications.

Instructor(s):
Level: intermediate/advanced

Who Should Take This Course:

Statisticians and data analysts who perform statistical inference, or need to assess uncertainty in their data. Those working with data that does not meet the distributional requirements of standard statistical procedures, or with unusual statistics or complex estimators will find the course particularly useful.

See also: Introduction to Resampling Methods

Dates:
To be scheduled.
bootsrap Click here to be reminded of future sessions of this course.

Registration:
Please read the syllabus tab, noting the prerequisites, text and software requirements.

Register Online -$499
Register Online -$399 (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.

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. Multiple course registrations may be entitled to tuition discounts; read more.

Share This :

Bootstrap Methods

taught by Michael Chernick
and Robert LaBudde

Aim of Course:

This course covers the basic theory and application of the bootstrap family of procedures, with the emphasis on applications. After taking this course, participants will be able to use the bootstrap procedure to assess bias and variance, test hypotheses, and produce confidence intervals. The bootstrap is illustrated also for regression and time series procedures. Basic and improved bootstrap procedures are covered.

Prerequisite(s):

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

Also:  Introduction to Resampling, which provides a non-statistician's perspective on basic bootstrapping.

Use of statistical software is important in this course -- please read the software section below for additional information on software requirements.

Course Program:

SESSION 1: Introduction

• Wide range of application
• Historical notes
• Bias estimation
  • Efron's patch data example
  • Estimating other parameters of a distribution

SESSION 2: Parameter Estimation

• Bias estimation (continued)
  • Error rate estimation problems
• Confidence intervals and hypothesis test
  • Percentile method confidence intervals
  • Higher order bootstrap confidence intervals
  • A 1-1 relationship between confidence intervals and hypothesis tests
  • Problems with bootstrap confidence intervals for variances

SESSION 3: Regression, Time Series, Which Methods?

• Linear Regression, bootstrap residuals or vectors
  • Non-linear Regression
    • A Quasi-optical experiment
  • Nonparametric Regression
    • Cox Model
    • CART
    • Bootstrap Bagging
  • Time Series Analysis
    • Model-based vs block resampling
  • Bootstrap variants
    • Bayesian bootstrap
    • Smoothed bootstrap
    • Parametric bootstrap
    • Iterated bootstrap
  • Number of repetitions (replications)

SESSION 4: Special Topics, Bootstrap Failures and Remedies

• Spatial data: kriging
• Subset selection
  • Examples of Gong and Gunter
• p-value adjustment
• Process capability indices
• Bioequivalence
• Failure Due to Small Sample Size
• Failure Due to Infinite Moments and Remedy (introducing m-out-of-n bootstrap)
• Failure Due to Estimating Extremes and Remedies

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 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:

The required text for this course is An Introduction to Bootstrap Methods with Applications to R by Michael Chernick and Robert LaBudde, and it can be ordered from Wiley by clicking here. Wiley typically offers statistics.com customers up to 15% discount on this book (and all other statistics titles): enter the code aff15 in the Promotion Code field when prompted during checkout and click the Apply Discount button. (If you are located in Asia, the web procedure for your location may not accept this discount – try calling your regional Wiley representative.).

PLEASE ORDER YOUR COPY IN TIME FOR THE COURSE STARTING DATE.

Software:

You must have a copy of R for the course.  Click Here for information on obtaining a free copy.  If you are not familiar with R, you should take one of statistics.com's "Introduction to R" courses:  either Introduction to R - Data Handling or Introduction to R - Statistics.

Register Now

Yes, I want to register for:

Bootstrap Methods

taught by Michael Chernick
and Robert LaBudde

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.

I am affiliated with an academic institution
I am not affiliated with an academic institution