This is an archived course. A more recent version may be available at ocw.mit.edu.
Lectures: 3 sessions / week, 1 hour / session
This course is a broad treatment of statistics, concentrating on specific statistical techniques used in science and industry. Topics include: hypothesis testing and estimation, confidence intervals, chi-square tests, nonparametric statistics, analysis of variance, regression, correlation, decision theory, and Bayesian statistics.
Probability and Random Variables (18.440) or Probabilistic Systems Analysis (6.041) or the equivalent (one semester of calculus-based probability). The prerequisite material is also covered in the required textbook (see below), Chapters 1-5.
Rice, John A. Mathematical Statistics and Data Analysis. 3rd ed. Belmont, CA: Duxbury Press, 2006. ISBN: 9780534399429.
We will cover material from Chapters 6 to 15 of the book. Some supplements will be made available as we go along. We will review probability as needed.
From fall 2003 through spring 2009, 18.443 has been taught in different flavors in the fall and spring. In the fall, it has been relatively more parametric or indeed Bayesian (a probability distribution being assumed a priori on the unknown parameters). The Bayesian textbook by DeGroot and Schervish ( DeGroot, Morris H., and Mark J. Schervish. Probability and Statistics. 3rd ed. Reading, MA: Pearson Addison Wesley. ISBN: 9780201524888.) has been assigned although not necessarily closely followed.
In the spring, the textbook by J. Rice (see above), which is relatively less parametric and has only a small amount of Bayesian material, has been assigned. Some supplementary Bayesian material has been included in the course.
A special feature of the Fall 2006 version by Professor Panchenko was the use of Mathematica.
There will be 10 problem sets. None will be due in weeks when there are exams.
There will not be a final exam. During the term there will be three exams, equally spaced during the course.
| ACTIVITIES | PERCENTAGES |
|---|---|
| Three exams (25% each) | 75% |
| Problem sets | 25% |
MIT OpenCourseWare makes the materials used in the teaching of almost all of MIT's subjects available on the Web, free of charge. With more than 2,200 courses available, OCW is delivering on the promise of open sharing of knowledge. Learn more »
© 2001–2015
Massachusetts Institute of Technology
Your use of the MIT OpenCourseWare site and materials is subject to our Creative Commons License and other terms of use.
Subscribe to the OCW Newsletter
