This is the first quarter of a two-quarter sequence. Enrollment in the first quarter alone is permitted, although not recommended. The first quarter will cover the basics -- tools from probability and the elements of statistical theory. Topics will include the definitions of probability and random variables, binomial and other discrete probability distributions, normal and other continuous probability distribution, joint probability distributions and the transformation of random variables, principles of inference (including Bayesian inference), maximum likelihood estimation, hypothesis testing and confidence intervals, likelihood ratio tests, multinomial distributions and chi-square tests. Some large sample theory will be included. The emphasis will be upon statistical theory, specifically upon concepts and tools that are useful for understanding and applying statistical methodology. Examples will be drawn from the social, physical, and biological sciences. There is no enforced prerequisite in probability or statistics, although the pace is such that students may find it useful to have taken a previous elementary course. The coverage of topics in probability will be limited and brief, so that those who have taken a course in probability will find reinforcement rather than redundancy. The second quarter will cover statistical methodology, including some multivariate analysis, the analysis of variance, the regression phenomenon, linear regression analysis, data analysis, and correlation. The computer will be used in the second quarter.

Prerequisites:
Calculus, including some familiarity with multivariate integration, and some familiarity with linear algebra (e.g. Math 19600 or 20100 or 20400, or equivalent). Some previous experience with statistics is recommended but not required.

Text (Recommended):
Detailed notes will be distributed in the first quarter. The recommended (but not required in the first quarter) text is Mathematical Statistics and Data Analysis (2nd edition, 1995), by John A. Rice (Duxbury).