Introduction to Resampling Methods

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.

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.

$799 | Enroll Now
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Overview

Resampling is a statistical method used to analyze data or statistics that are not suitable for standard analysis. The approach of this 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.

Introductory/Intermediate Level
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Learning Outcomes

Students who complete this course will gain a basic knowledge of the resampling approach to inference,  how to work with count data, and techniques for working with multivariate data.

  • Specify the resampling algorithms for hypothesis tests and confidence intervals
  • Use software to test hypotheses and derive confidence intervals
  • Describe the difference between a permutataion procedure and a bootstrap
  • Apply resampling to correlation and regression
  • Describe the relationship between resampling and standard formula approaches

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.

Instructors

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Mr. Peter Bruce

Mr. Peter Bruce

Mr. Peter Bruce is Founder and President of The Institute for Statistics Education at Statistics.com. He is the developer of Resampling Stats software (originated by Julian Simon in the 1970's), and has also taught resampling statistics at the University of Maryland and in a variety of short courses. He is the author of Responsible Data Science, with Grant Fleming (Wiley, 2021), Machine Learning for Business Analytics, with Galit Shmueli, Peter Gedeck,

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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.

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Course Syllabus

Week 1

The Resampling Approach to Inference

  • Historical perspective
  • Hypothesis tests vs. 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

Week 2

Working with Count Data

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

Week 3

Working with Multivariate Data

  • ANOVA
  • Correlation
  • Regression

Week 4

There is no instruction this week.

Class Dates

2023

No classes scheduled at this time.

2024

Mar 1, 2024 to Mar 22, 2024

2025

No classes scheduled at this time.

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Prerequisites

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.

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What Our Students Say​

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Left Square Qoute

I found the course to be a valuable introduction to resampling and bootstrapping methods. I am recommending this course to colleagues. Thanks for an engaging and informative course.

Jay Thomas
Pacific University
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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

Related Courses

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Mapping in R Course

Bootstrap Methods

This course will teach you the basic theory and application of the bootstrap family of procedures with the emphasis on applications.
Topic: Statistics, Statistical Modeling | Skill: Intermediate, Advanced | Credit Options: CEU
Class Start Dates: Sep 22, 2023, Sep 20, 2024

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 3-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 supplemental readings available online, discussion tasks, and example software codes.

Course Text

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

Software

Course illustrations and exercises will be provided in R, and also in Resampling Stats for Excel.

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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Introduction to Resampling Methods
$799 | Enroll Now
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