Bootstrapping and Resampling in Statistics with Example| Statistics Tutorial #12 |MarinStatsLectures
Bootstrapping and Resampling in Statistics with Example: What is Bootstrapping in Statistics and Why Do We Use it? 👉🏼Related Videos: Bootstrapping in Statistics & Bootstrapping in R Series:
👍🏼Best Statistics & R Programming Language Tutorials: ( )
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▶︎ In this statistics video lecture we will learn the Bootstrap method (a brute force method), along with why one may want to use such an approach.
▶︎ Bootstrap in statistics is a re-sampling based approach, useful for estimating the sampling distribution and standard error of an estimate. Bootstrapping provides an alternative approach to approaches based on large sample theory (you may recall that many approaches rely on having a large n in order to carry out the method).
▶︎ Bootstrapping in statistics and in research becomes particularly useful when dealing with more complicated estimates, where their standard error may not be easily calculated.
▶︎ This video takes a simple example, and explains the principle of a bootstrap approach, and the concept it is based on. The intention is to clarify exactly what this method involves. This video uses an estimate of a “sample mean“ for simplicity of explaining the concept, although the bootstrap’s real value comes when dealing with more complicated , we simply aim to provide a conceptual understanding of this approach.
► ► Watch More:
► Intro to Statistics Course:
►Data Science with R
►Getting Started with R (Series 1):
►Graphs and Descriptive Statistics in R (Series 2):
►Probability distributions in R (Series 3):
►Bivariate analysis in R (Series 4):
►Linear Regression in R (Series 5):
►ANOVA Concept and with R
►Hypothesis Testing:
►Linear Regression Concept and with R Lectures
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Content Creator: Mike Marin (., MSc.) Senior Instructor at UBC.
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These videos are created by #marinstatslectures to support some statistics and R programming language courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free.
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