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<a class="navbar-brand" href="week37-bs.html">Week 37: Statistical interpretations and Resampling Methods</a>
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<!-- navigation toc: --> <li><a href="._week37-bs001.html#plans-for-week-37" style="font-size: 80%;">Plans for week 37</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs002.html#material-from-last-week-and-relevant-for-the-weekly-exercises" style="font-size: 80%;">Material from last week and relevant for the weekly exercises</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs003.html#linking-the-regression-analysis-with-a-statistical-interpretation" style="font-size: 80%;">Linking the regression analysis with a statistical interpretation</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs004.html#assumptions-made" style="font-size: 80%;">Assumptions made</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs005.html#expectation-value-and-variance" style="font-size: 80%;">Expectation value and variance</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs006.html#expectation-value-and-variance-for-boldsymbol-beta" style="font-size: 80%;">Expectation value and variance for \( \boldsymbol{\beta} \)</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs007.html#material-for-lecture-thursday-september-14" style="font-size: 80%;">Material for lecture Thursday September 14</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs008.html#deriving-ols-from-a-probability-distribution" style="font-size: 80%;">Deriving OLS from a probability distribution</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs009.html#independent-and-identically-distrubuted-iid" style="font-size: 80%;">Independent and Identically Distrubuted (iid)</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs010.html#maximum-likelihood-estimation-mle" style="font-size: 80%;">Maximum Likelihood Estimation (MLE)</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs011.html#a-new-cost-function" style="font-size: 80%;">A new Cost Function</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs012.html#more-basic-statistics-and-bayes-theorem" style="font-size: 80%;">More basic Statistics and Bayes' theorem</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs013.html#marginal-probability" style="font-size: 80%;">Marginal Probability</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs014.html#conditional-probability" style="font-size: 80%;">Conditional Probability</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs015.html#bayes-theorem" style="font-size: 80%;">Bayes' Theorem</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs016.html#interpretations-of-bayes-theorem" style="font-size: 80%;">Interpretations of Bayes' Theorem</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs017.html#example-of-usage-of-bayes-theorem" style="font-size: 80%;">Example of Usage of Bayes' theorem</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs018.html#doing-it-correctly" style="font-size: 80%;">Doing it correctly</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs019.html#bayes-theorem-and-ridge-and-lasso-regression" style="font-size: 80%;">Bayes' Theorem and Ridge and Lasso Regression</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs020.html#ridge-and-bayes" style="font-size: 80%;">Ridge and Bayes</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs021.html#lasso-and-bayes" style="font-size: 80%;">Lasso and Bayes</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs025.html#why-resampling-methods" style="font-size: 80%;">Why resampling methods</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs027.html#resampling-methods" style="font-size: 80%;">Resampling methods</a></li>
<!-- navigation toc: --> <li><a href="#resampling-approaches-can-be-computationally-expensive" style="font-size: 80%;">Resampling approaches can be computationally expensive</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs025.html#why-resampling-methods" style="font-size: 80%;">Why resampling methods ?</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs026.html#statistical-analysis" style="font-size: 80%;">Statistical analysis</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs027.html#resampling-methods" style="font-size: 80%;">Resampling methods</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs028.html#resampling-methods-bootstrap" style="font-size: 80%;">Resampling methods: Bootstrap</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs029.html#the-central-limit-theorem" style="font-size: 80%;">The Central Limit Theorem</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs030.html#finding-the-limit" style="font-size: 80%;">Finding the Limit</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs031.html#rewriting-the-delta-function" style="font-size: 80%;">Rewriting the \( \delta \)-function</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs032.html#identifying-terms" style="font-size: 80%;">Identifying Terms</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs033.html#wrapping-it-up" style="font-size: 80%;">Wrapping it up</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs034.html#confidence-intervals" style="font-size: 80%;">Confidence Intervals</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs035.html#standard-approach-based-on-the-normal-distribution" style="font-size: 80%;">Standard Approach based on the Normal Distribution</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs036.html#resampling-methods-bootstrap-background" style="font-size: 80%;">Resampling methods: Bootstrap background</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs037.html#resampling-methods-more-bootstrap-background" style="font-size: 80%;">Resampling methods: More Bootstrap background</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs038.html#resampling-methods-bootstrap-approach" style="font-size: 80%;">Resampling methods: Bootstrap approach</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs039.html#resampling-methods-bootstrap-steps" style="font-size: 80%;">Resampling methods: Bootstrap steps</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs040.html#code-example-for-the-bootstrap-method" style="font-size: 80%;">Code example for the Bootstrap method</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs041.html#plotting-the-histogram" style="font-size: 80%;">Plotting the Histogram</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs042.html#the-bias-variance-tradeoff" style="font-size: 80%;">The bias-variance tradeoff</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs043.html#a-way-to-read-the-bias-variance-tradeoff" style="font-size: 80%;">A way to Read the Bias-Variance Tradeoff</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs044.html#example-code-for-bias-variance-tradeoff" style="font-size: 80%;">Example code for Bias-Variance tradeoff</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs045.html#understanding-what-happens" style="font-size: 80%;">Understanding what happens</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs046.html#summing-up" style="font-size: 80%;">Summing up</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs047.html#another-example-from-scikit-learn-s-repository" style="font-size: 80%;">Another Example from Scikit-Learn's Repository</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs048.html#various-steps-in-cross-validation" style="font-size: 80%;">Various steps in cross-validation</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs049.html#cross-validation-in-brief" style="font-size: 80%;">Cross-validation in brief</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs050.html#code-example-for-cross-validation-and-k-fold-cross-validation" style="font-size: 80%;">Code Example for Cross-validation and \( k \)-fold Cross-validation</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs051.html#more-examples-on-bootstrap-and-cross-validation-and-errors" style="font-size: 80%;">More examples on bootstrap and cross-validation and errors</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs052.html#the-same-example-but-now-with-cross-validation" style="font-size: 80%;">The same example but now with cross-validation</a></li>
<!-- navigation toc: --> <li><a href="._week37-bs052.html#notes-on-scaling-with-examples" style="font-size: 80%;">Notes on scaling with examples</a></li>
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<h2 id="resampling-approaches-can-be-computationally-expensive" class="anchor">Resampling approaches can be computationally expensive </h2>
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<p>Resampling approaches can be computationally expensive, because they
involve fitting the same statistical method multiple times using
different subsets of the training data. However, due to recent
advances in computing power, the computational requirements of
resampling methods generally are not prohibitive. In this chapter, we
discuss two of the most commonly used resampling methods,
cross-validation and the bootstrap. Both methods are important tools
in the practical application of many statistical learning
procedures. For example, cross-validation can be used to estimate the
test error associated with a given statistical learning method in
order to evaluate its performance, or to select the appropriate level
of flexibility. The process of evaluating a model&#8217;s performance is
known as model assessment, whereas the process of selecting the proper
level of flexibility for a model is known as model selection. The
bootstrap is widely used.
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