Bootstrap Methods

Bootstrap Methods

This course will teach you the basic theory and application of the bootstrap family of procedures with the emphasis on applications.

This course will teach you the basic theory and application of the bootstrap family of procedures with the emphasis on applications.

$999 | Enroll Now
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Overview

This course, designed for Statisticians and data analysts who perform statistical inference or need to assess uncertainty in their data, covers the basic theory and application of the bootstrap family of procedures with an emphasis on applications. It also illustrates bootstrap for regression and time series procedures. Students should be familiar with introductory statistics, and must have a working installation of the R statistical software package.

Intermediate/Advanced Level
100% Online Courses
4-Week Course
Expert Instructors
Teacher Assistant Support
Tution-Back Guarantee

Learning Outcomes

After taking this course, participants will be able to use the bootstrap procedure to assess bias and variance, test hypotheses, and produce confidence intervals.

  • Use the bootstrap to estimate bias
  • Construct confidence intervals using the bootstrap
  • Apply the bootstrap to linear regressions
  • Apply the bootstrap to time series analysis
  • Make appropriate use of bootstrap variants

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.

Instructors

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Dr. Robert Labuddle

Dr. Robert LaBudde

Dr. Robert LaBudde is president and founder of Least Cost Formulations, Ltd., a mathematical software development company specializing in optimization and process control software for manufacturing companies. He has served on the faculties of the University of Wisconsin, Massachusetts Institute of Technology, Old Dominion University and North Carolina State University. Dr. LaBudde is currently Adjunct Professor of Statistics at Old Dominion University.

See Instructor Bio

Course Syllabus

Week 1

Introduction

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

Week 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

Week 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)

Week 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

Class Dates

2023

Sep 22, 2023 to Oct 20, 2023

2024

Sep 20, 2024 to Oct 18, 2024

2025

No classes scheduled at this time.

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Prerequisites

There are no prerequisites for this course.

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

Introductory Statistics

We assume you are versed in statistics or have the equivalent understanding of topics covered in our Statistics 1 and Statistics 2 courses. but do not require them as eligibility to enroll in this course. Please review the course description for each of our introductory statistics courses, estimate which best matches your level of understanding of the material covered in these courses, then take the short assessment test for that course. If you can not answer more than half of the questions correctly, we suggest you take our Statistics 1 and Statistics 2 courses prior to taking this course.

After your self-assessment, review our course, Introduction to Resampling, which provides a non-statistician’s perspective on basic bootstrapping, and then decide which course is right for you.

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Introduction to Resampling Methods

The course introduces the basic concepts and methods of resampling methods including bootstrap procedures and permutation with little or no complex theory or confusing notation.
Topic: Statistics, Statistical Modeling | Skill: Introductory, Intermediate | Credit Options: CEU
Class Start Dates: Mar 1, 2024

What Our Students Say​

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Left Square Qoute

I learned that there are several ways to use bootstrap. The course is an excellent starting point for anyone working with this methodology. I intend to use bootstrap in spatial analysis.

Gustavo Dalposso
Professor, Universidade Estadual do Oeste do Paraná
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Left Square Qoute

I thought the notes were fantastic - very clear, and interesting. One of the best courses I've ever taken!

Sofia Auer
Data Scientist at National Research Council Canada
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Frequently Asked Questions

Can I transfer or withdraw from a course?

We have a flexible transfer and withdrawal policy that recognizes circumstances may arise to prevent you from taking a course as planned. You may transfer or withdraw from a course under certain conditions.
  • Students are entitled to a full refund if a course they are registered for is canceled.
  • You can transfer your tuition to another course at any time prior to the course start date or the drop date, however a transfer is not permitted after the drop date.
  • Withdrawals on or after the first day of class are entitled to a percentage refund of tuition.
Please see this page for more information.

Who are the instructors at the Institute?

The Institute has more than 60 instructors who are recruited based on their expertise in various areas in statistics. Our faculty members are:

  • Authors of well-regarded texts in their area;
  • Advisory board members;
  • Senior faculty; and
  • Educators who have made important contributions to the field of statistics or online education in statistics.

The majority of our instructors have more than five years of teaching experience online at the Institute.

Please visit our faculty page for more information on each instructor at The Institute for Statistics Education.

Please see our knowledge center for more information.

What type of courses does the Institute offer?

The Institute offers approximately 80 courses each year. Topics include basic survey courses for novices, a full sequence of introductory statistics courses, bridge courses to more advanced topics. Our courses cover a range of topics including biostatistics, research statistics, data mining, business analytics, survey statistics, and environmental statistics.

Please see our course search or knowledge center for more information.

Do your courses have for-credit options?

Our courses have several for-credit options:

  • Continuing education units (CEU)
  • College credit through The American Council on Education (ACE CREDIT)
  • Course credits that are transferable to the INFORMS Certified Analytics Professional (CAP®)

Please see our knowledge center for more information.

Is the Institute for Statistics Education certified?

The Institute for Statistics Education is certified to operate by the State Council of Higher Education for Virginia (SCHEV). For more information visit: https://www.schev.edu/

Please see our knowledge center for more information.

Visit our knowledge base and learn more.

FAQs + Knowledge Base

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Additional Course Information

Organization of Course

This course takes place online 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.

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.

Time Requirements

This is a 4-week course requiring 10-15 hours per week of review and study, at times of your choosing.

Homework

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

In addition to assigned readings, this course also has and an exam.

Course Text

The required text for this course is An Introduction to Bootstrap Methods with Applications to R by Michael Chernick and Robert LaBudde.

Please order a copy of your course textbook prior to course start date.

Software

You must have a copy of R for the course. If you are not familiar with R, you should consider taking our “Introduction to R” courses:

Software Uses and Descriptions | Available Free Versions
To learn more about the software used in this course, or how to obtain free versions of software used in our courses, please read our knowledge base article “What software is used in courses?” 

Course Fee & Information

Enrollment
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.

Transfers and Withdrawals
We have flexible policies to transfer to another course or withdraw if necessary.

Group Rates
Contact us to get information on group rates.

Discounts
Academic affiliation?  In most courses you are eligible for a discount at checkout.

New to Statistics.com?  Click here for a special introductory discount code.  

Invoice or Purchase Order
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.

Options for Credit and Recognition

This course is eligible for the following credit and recognition options:

No Credit
You may take this course without pursuing credit or a record of completion.

Mastery or Certificate Program Credit
If you are enrolled in mastery or certificate program that requires demonstration of proficiency in this subject, your course work may be assessed for a grade.

CEUs and Proof of Completion
If you require a “Record of Course Completion” along with professional development credit in the form of Continuing Education Units (CEU’s), upon successfully completing the course, CEU’s and a record of course completion will be issued by The Institute upon your request.

Supplemental Information

Literacy, Accessibility, and Dyslexia

At Statistics.com, we aim to provide a learning environment suitable for everyone. To help you get the most out of your learning experience, we have researched and tested several assistance tools. For students with dyslexia, colorblindness, or reading difficulties, we recommend the following web browser add-ons and extensions:

 

Chrome

 

Firefox

 

Safari

  • Navidys (for colorblindness, dyslexia, and reading difficulties)
  • HelperBird for Safari (for colorblindness, dyslexia, and reading difficulties)

Miscellaneous

There is no additional information for this course.

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Bootstrap Methods
$999 | Enroll Now
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