RES.TLL004 STEM Concept Videos  Probability and Statistics
http://ocw.mit.edu/resources/restll004stemconceptvideosfall2013/videos/probabilityandstatistics
20150315T18:14:09+05:00
MIT OpenCourseWare http://ocw.mit.edu
enUS
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (AttributionNonCommercialShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Conditional Probability
<h2 class="subhead">Summary</h2> <p>This video provides an introduction to conditional probability and its calculations. The first chapter reviews basic probability terminology and introduces standard conditional probability notation using a simple marble drawing example. The second chapter introduces the use of tree diagrams to help visualize the sample space and allow for more complex probability calculations. In the last chapter, we see how conditional probability can and must be used to make sense of medical diagnoses.</p> <h2 class="subhead">Learning Objectives</h2> <p>After watching this video students will be able to:</p> <ul> <li>Calculate the conditional probability of a given event using tables and trees.</li> <li>Understand how conditional probability can be used to interpret medical diagnoses.</li> </ul> <p>Funding provided by the Singapore University of Technology and Design (SUTD)</p> <p>Developed by the Teaching and Learning Laboratory (TLL) at MIT for SUTD</p> <p>MIT © 2012</p>Keywords: conditional probability, tables, probability, outcomes, sample space, condition, tree diagram<br><br>Subtitles: <a href= English  US>SRT</a><br>Thumbnail  <a href= http://img.youtube.com/vi/JGeTcRfKgBo/default.jpg>JPG (YouTube)</a><br>Video  download: <a href= http://www.archive.org/download/MITRES.TLL004F13/MITRES_TLL004F13_conditional_probabilty_300k.mp4>Internet Archive (MP4)</a><br>Video  download: <a href= https://itunes.apple.com/us/podcast/conditionalprobability/id765926614?i=237394829&mt=2>iTunes U (MP4)</a><br>Video  stream: <a href= http://www.youtube.com/v/JGeTcRfKgBo>YouTube </a><br><br><a href= 'http://ocw.mit.edu/terms/'>(CC BYNCSA)</a><br><br>
http://ocw.mit.edu/resources/restll004stemconceptvideosfall2013/videos/probabilityandstatistics/conditionalprobability
Teaching and Learning Laboratory (TLL)
Singapore University of Technology and Design (SUTD)
20131230T16:02:35+05:00
enUS
conditional probability
tables
probability
outcomes
sample space
condition
tree diagram
MIT OpenCourseWare http://ocw.mit.edu
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (AttributionNonCommercialShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Diffusion and Fick's Law
<h2 class="subhead">Summary</h2><p>This video uses a simple model to help students understand the fundamental difference between a regular and a random walk. The concept of a random walk is connected to diffusion and is used to explain the structure of Fick's law. Finally, Fick's Law is used to explain why wearing a coat is useful in the winter, to estimate diffusion times for biomolecules, and to understand why we need a circulatory system to efficiently transport oxygen throughout the body.</p><h2 class="subhead">Learning Objectives</h2><p>After watching this video students will be able to:</p><ul><li>Describe the difference between regular and random walks.</li><li>Explain the structure of Fick's law.</li></ul><p>Funding provided by the Singapore University of Technology and Design (SUTD)</p><p>Developed by the Teaching and Learning Laboratory (TLL) at MIT for SUTD</p><p>MIT © 2012</p>Subtitles: <a href= English  US>SRT</a><br>Thumbnail  <a href= http://img.youtube.com/vi/w4y12u5S0HE/default.jpg>JPG (YouTube)</a><br>Video  download: <a href= http://www.archive.org/download/MITRES.TLL004F13/MITRES_TLL004F13_diffusion_300k.mp4>Internet Archive (MP4)</a><br>Video  download: <a href= https://itunes.apple.com/us/itunesu/id765926614>iTunes U (MP4)</a><br>Video  stream: <a href= http://www.youtube.com/v/w4y12u5S0HE>YouTube </a><br><br><a href= 'http://ocw.mit.edu/terms/'>(CC BYNCSA)</a><br><br>
http://ocw.mit.edu/resources/restll004stemconceptvideosfall2013/videos/probabilityandstatistics/diffusionandfickslaw
Teaching and Learning Laboratory (TLL)
Singapore University of Technology and Design (SUTD)
20131230T16:02:35+05:00
enUS
MIT OpenCourseWare http://ocw.mit.edu
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (AttributionNonCommercialShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Genetics and Statistics
<h2 class="subhead">Summary</h2> <p>This video introduces students to Chi square hypothesis testing. The Chi square test for goodness of fit is used to analyze experimental data from a basic coin flipping experiment. Students then use what they learned to better understand experimental data obtained from genetic experiments.</p> <h2 class="subhead">Learning Objectives</h2> <p>After watching this video students will be able to apply Chi square hypothesis testing to experimental data obtained from genetic experiments.</p> <p>Funding provided by the Singapore University of Technology and Design (SUTD)</p> <p>Developed by the Teaching and Learning Laboratory (TLL) at MIT for SUTD</p> <p>MIT © 2012</p>Keywords: probability distributions, Chi Square Test for Goodness of Fit, null hypothesis, alternative hypothesis, level of significance, wingless phenotype, wildtype winged phenotype, Punnett square, progeny, wildtype, mutant<br><br>Transcript: <a href= /resources/restll004stemconceptvideosfall2013/videos/probabilityandstatistics/geneticsandstatistics/MITRES_TLL004F13_Genetics.pdf>PDF</a><br>Subtitles: <a href= English  US>SRT</a><br>Thumbnail  <a href= http://img.youtube.com/vi/IWKPe6X6Vs/default.jpg>JPG (YouTube)</a><br>Video  download: <a href= https://archive.org/download/MITRES.TLL004F13/MITRES_TLL004F13_genetics_and_statistics_300k.mp4>Internet Archive (MP4)</a><br>Video  download: <a href= https://itunes.apple.com/us/podcast/geneticsandstatistics/id765926614?i=317672231&mt=2>iTunes U (MP4)</a><br>Video  stream: <a href= http://www.youtube.com/v/IWKPe6X6Vs>YouTube </a><br><br><a href= 'http://ocw.mit.edu/terms/'>(CC BYNCSA)</a><br><br>
http://ocw.mit.edu/resources/restll004stemconceptvideosfall2013/videos/probabilityandstatistics/geneticsandstatistics
Teaching and Learning Laboratory (TLL)
Singapore University of Technology and Design (SUTD)
20131230T16:02:35+05:00
enUS
probability distributions
Chi Square Test for Goodness of Fit
null hypothesis
alternative hypothesis
level of significance
wingless phenotype
wildtype winged phenotype
Punnett square
progeny
wildtype
mutant
MIT OpenCourseWare http://ocw.mit.edu
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (AttributionNonCommercialShareAlike). For further information see http://ocw.mit.edu/terms/index.htm

Moments of Distributions
<h2 class="subhead">Summary</h2> <p>This video introduces students to the moments of a distribution and how they can be used to characterize the shape of a distribution. Students apply what they learned to examples of discrete and continuous distributions.</p> <h2 class="subhead">Learning Objectives</h2> <p>After watching this video students will be able to:</p> <ul> <li>Explain moments of distributions.</li> <li>Compute moments and understand what they mean.</li> </ul> <p>Funding provided by the Singapore University of Technology and Design (SUTD)</p> <p>Developed by the Teaching and Learning Laboratory (TLL) at MIT for SUTD</p> <p>MIT © 2012</p>Keywords: integration, probabilities, probability distribution, moments of a distribution, mean, variance, expected value, first moment, second moment, parallel axis theorem, continuous distributions, dispersion, standard deviation<br><br>Transcript: <a href= /resources/restll004stemconceptvideosfall2013/videos/probabilityandstatistics/momentsofdistributions/MITRES_TLL004F13_MmntDist.pdf>PDF</a><br>Subtitles: <a href= English  US>SRT</a><br>Thumbnail  <a href= http://img.youtube.com/vi/fv5QB3eK7jA/default.jpg>JPG (YouTube)</a><br>Video  download: <a href= https://archive.org/download/MITRES.TLL004F13/MITRES_TLL004F13_moments_of_distributions_300k.mp4>Internet Archive (MP4)</a><br>Video  download: <a href= https://itunes.apple.com/us/podcast/momentsofdistributions/id765926614?i=317672235&mt=2>iTunes U (MP4)</a><br>Video  stream: <a href= http://www.youtube.com/v/fv5QB3eK7jA>YouTube </a><br><br><a href= 'http://ocw.mit.edu/terms/'>(CC BYNCSA)</a><br><br>
http://ocw.mit.edu/resources/restll004stemconceptvideosfall2013/videos/probabilityandstatistics/momentsofdistributions
Teaching and Learning Laboratory (TLL)
Singapore University of Technology and Design (SUTD)
20131230T16:02:35+05:00
enUS
integration
probabilities
probability distribution
moments of a distribution
mean
variance
expected value
first moment
second moment
parallel axis theorem
continuous distributions
dispersion
standard deviation
MIT OpenCourseWare http://ocw.mit.edu
Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (AttributionNonCommercialShareAlike). For further information see http://ocw.mit.edu/terms/index.htm