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<p class="MsoNormal">I have a professor looking to move to LON-CAPA for her IE 230 course in the fall. She has 2 grad students getting ready to start coding problems, but I thought I’d take a shot at tossing out a feeler for domains using this type of content
already. Here is how she described her course.<o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoPlainText">“The best way to describe the course to people who teach probability and statistics is that we cover the first half of Montgomery and Runger. This is a fairly common / well-known text. It is introductory probability for engineers with
calculus. (Calc 3 is a co-requisite for the course.)<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">The short list of topics is:<o:p></o:p></p>
<p class="MsoPlainText">- Review of sets<o:p></o:p></p>
<p class="MsoPlainText">- Sample spaces and events<o:p></o:p></p>
<p class="MsoPlainText">- Event probabilities and the three Axioms of Probability<o:p></o:p></p>
<p class="MsoPlainText">- Conditional probability and independence, including the Law of Total Probability and Bayes Rule<o:p></o:p></p>
<p class="MsoPlainText">- Intro to random variables (r.v.’s)<o:p></o:p></p>
<p class="MsoPlainText">- pmf / cdf / mean / variance for discrete r.v.’s<o:p></o:p></p>
<p class="MsoPlainText">- Common discrete distributions: Bernoulli, binomial, geometric, negative binomial, hypergeometric<o:p></o:p></p>
<p class="MsoPlainText">- pdf / cdf / mean / variance for continuous r.v.’s<o:p></o:p></p>
<p class="MsoPlainText">- Common continuous distributions: uniform, triangular, normal, exponential, gamma, intro to Poisson Processes<o:p></o:p></p>
<p class="MsoPlainText">- Bivariate discrete and continuous r.v.’s<o:p></o:p></p>
<p class="MsoPlainText">- Bivariate distributions and independence / expected values / marginal / covariance / correlation<o:p></o:p></p>
<p class="MsoPlainText">- Bivariate normal distributions<o:p></o:p></p>
<p class="MsoPlainText">- Distributions for more than 2 r.v.’s<o:p></o:p></p>
<p class="MsoPlainText">- Estimation: mean, variance, difference of means, bias, standard error, SLLN, CLT, Maximum Likelihood functions and estimators”<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoPlainText">Any help would be greatly appreciated!<o:p></o:p></p>
<p class="MsoPlainText"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">David Huckleberry<o:p></o:p></p>
<p class="MsoNormal">Educational Technologist<o:p></o:p></p>
<p class="MsoNormal">Innovations in Teaching and Learning<o:p></o:p></p>
<p class="MsoNormal">Purdue University<o:p></o:p></p>
<p class="MsoNormal"><b><span style="font-size:10.0pt;font-family:Helvetica-Light;color:red">NEW!</span></b><span style="font-size:10.0pt;font-family:Helvetica-Light;color:black">
<a href="https://www.itap.purdue.edu/learning/services/consultation-requests.html">
<span style="color:#0563C1">Coffee Break Consultations!</span></a></span><u><span style="font-size:10.0pt;font-family:Helvetica-Light;color:#0563C1"><o:p></o:p></span></u></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
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