300. Introduction to Statistical Reasoning. (NS).
This course is designed to provide an overview of the field of statistics. Course topics include methods of analyzing and summarizing data, statistical reasoning as a means of learning from observations (experimental or sample), and techniques for dealing with uncertainties in drawing conclusions from collected data. Basic fallacies in common statistical analyses and reasoning are discussed and proper methods indicated. Alternative approaches to statistical inference are also discussed. The course emphasis is on presenting basic underlying concepts rather than on covering a wide variety of different methodologies. Evaluation is based upon a midterm and a final examination. The course format is lecture with some discussion.
412. Introduction to Probability and Statistics. Prior or concurrent enrollment in Math. 215 and either CS 283 or Engin. 102. No credit granted to those who have completed 311 or 402. (NS).
The objective of this course are to introduce students to the basic ideas of probability and statistical inference and to acquaint students with some important data analytic techniques, such as regression and the analysis of variance. Examples will emphasize applications to the natural sciences and engineering. There will be regular homework, including assignments which require the use of MTS, two midterms, and a final exam.
University of Michigan | College of LS&A | Student Academic Affairs | LS&A Bulletin Index
This page maintained by LS&A Academic Information and Publications, 1228 Angell Hall
of the University of Michigan,
Ann Arbor, MI 48109 USA +1 734 764-1817
Trademarks of the University of Michigan may not be electronically or otherwise altered or separated from this document or used for any non-University purpose.