16.470[J] Statistical Methods in Experimental Design


Class Info

Statistically based experimental design inclusive of forming hypotheses, planning and conducting experiments, analyzing data, and interpreting and communicating results. Topics include descriptive statistics, statistical inference, hypothesis testing, parametric and nonparametric statistical analyses, factorial ANOVA, randomized block designs, MANOVA, linear regression, repeated measures models, and application of statistical software packages.

This class has 6.041, and 16.09 as prerequisites.

16.470[J] will not be offered this semester. It will be instructed by L. A. Stirling.

This class counts for a total of 12 credits. This is a graduate-level class.

In the Spring 2014 Subject Evaluations, 16.470[J] was rated 5.8 out of 7.0. You can find more information at the Statistics at MIT - Classes site.

MIT 16.470[J] Statistical Methods in Experimental Design Related Textbooks
MIT 16.470[J] Statistical Methods in Experimental Design On The Web
Statistics at MIT - Classes
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models catalog statistics methods regression bayesian markov monte carlo kalman

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