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Lecture schedule --- R --- Info on students ---- Homework --- a few statistics links (under construction) -- selected references (under construction)
Current student information
Problem Set Five is due 28 march 2002.
This course is designed as a lecture course covering various topics in Statistical analysis (see below). I assume students have some modest background in statistics and we build on this by discussing a number of topics. The goal of this course is to provide students with a better feel for statistics and to be much less intimidated by methods of statistical analysis.
Course Objectives: We will introduce statistical distributions and computing the statistical power of various designs, matrix algebra useful for statistics and the general linear model, maximum likelihood estimation and testing, Bayesian Statistics, and various resampling and randomization methods. The focus is obtaining a general understanding of these statistical tools rather than which computer programs to use. Thus, the course will be somewhat more theoretical than applied, but the student will leave with a much broader understanding than a course concerned with running various statistical packages.
Math/Stats background required: Some knowledge of Calculus and a previous stats course (which introduced covariance, regression and ANOVA) is desirable.
Computer Programs: While the course focus is in basic statistical concepts, we will also introduce two programs:
Meeting time and Place: Tuesday and Thursday, 8:00 am - 9:15 a.m. BSW 237
Instructor: Bruce Walsh:
The R Project for statistical Computing website
US Mirror site for downloading R. Current versions for
An Introduction of R (Walsh notes)
pdf files of The official R Manuals
|10 Jan||Thursday||1||Overview: Probabilities, Variances, Covariances||(1): Univariate Distributions,|
|15 Jan||Tuesday||2||Normal, t, Chi-square, F distributions||(1): Distributions of functions of normals,|
|17 Jan||Thursday||3||Power of tests 1: Normals||Problem Set One due||(1): Power,|
|22 Jan||Tuseday||4||Power of tests 2: ANOVAs|
|24 Jan||Thursday||5||Matrix algebra 1: addition, multiplication||Problem Set Two due||Intro to Matrix Algebra and linear models|
|29 Jan||Tuseday||6||Matrix algebra 2: Inversion and the Multivariate Normal||Problem Set Three due||Matrix Calculations in R|
|31 Jan||Thursday||7||Matrix algebra 3: Eigenstructure. Principal Components||Eigenstructure Notes|
|5 Feb||Tuseday||8||General linear model (GLM)1: OLS||General linear models|
|7 Feb||Thursday||9||GLM 2: GLS||Problem Set Four due|
|12 Feb||Tuesday||10||GLM 3: hypothesis testing|
|14 Feb||Thursday||11||Walsh at NIH|
|19 Feb||Tuesday||12<||Generalized Linear Models||Generalized Linear Models|
|21 Feb||Tuesday||14||Mixed Models||Mixed Linear Models|
|26 Feb||Thursday||15||Maximum Likelihood (ML) 1: Introduction||MLE and Likelihood ratio tests|
|28 Feb||Tuesday||16||ML 2: likelihood ratio tests and asymptotics|
|5 March||Thursday||17||ML 3: Mixture models|
|12 march||Tuesday||Spring Break|
|14 March||Thursday||Spring Break|
|19 March||Tuesday||18||No Class|
|21 March||Thursday||19||No Class|
|26 March||Tuesday||20||No Class|
|28 March||Thursday||21||Resampling methods 1: Randomization and the Jackknife||Problem Set Five due||Resampling methods|
|2 April||Tuesday||22||Resampling methods 2: The Bootstrap|
|4 April||Thursday||23||Bayesian methods: 1: Introduction||Bayesian methods|
|9 April||Tuesday||24||Bayesian methods: 2 Posterior information|
|11 April||Thursday||25||Bayesian methods: 3: Estimation and hypothesis testing|
|16 April||Tuesday||26||Gibbs sampler: Bayesian applications||MCMC and Gibbs|
|18 April||Thursday||27||Bayesian methods: 3: Estimation and hypothesis testing|
|23 April||Tuesday||28||Gibbs sampler: Bayesian applications|
|25 April||Thursday||29||MCMC and Gibbs|
|30 April||Tuesday||30||Expectation-maximum (EM) methods 1: Treating missing data|
|Problem set||Topic||Due date||Solutions|
|1||Simple Regressions||17 Jan 2002||PS 1 Solutions|
|2||Power of Normal tests||24 Jan 2002||PS 2 Solutions|
|3||Power and Non-central Fs||29 Jan 2002||PS 3 Solutions|
|4||Multivariate normal calculations||7 Feb 2002||PS 4 Solutions|
|5||Univariate Maximum Likelihood||28 March 2002||PS 5 Solutions|
Statistical tables (from UCLA) -- // -- Other
StatLib site at the
Department of Statistics, Carnegie Mellon University.
A collection of fun data sets for analysis can be found in the
Journal of Statistics Education Data Archive
Home page for
RNR613: , Applied Biostatistics.
Selected Statistics Links
Selected Statistics References
On line Statistical tables (from UCLA) -- // -- Other statistical calculators
The StatLib site at the Department of Statistics, Carnegie Mellon University.
A collection of fun data sets for analysis can be found in the Journal of Statistics Education Data Archive
Home page for
RNR613: , Applied Biostatistics.