Learning : Introduction to Statistics
Learning : Introduction to Statistics
The various documentation, learning materials, short courses, and research manuscripts accessible on the RCTdesign webpages will at times make reference to the general behavior of particular statistical analysis models. We present here access to course materials that were developed by Scott Emerson, Professor Emeritus of Biostatistics, when he taught applied statistics and statistical theory for the Department of Biostatistics and the Department of Statistics during the years 1995 - 2017. These are merely presented as a resource for interested users. There should be no need for persons already having the required statistical knowledge to review this material. (These pages are truly presented primarily as a place for Professor Emerson to consolidate his course materials, and as such is a successor the EmersonStatistics.com website.)
Supplementary materials common to several courses
Datasets used in examples and homeworks
The Scientist Game
A presentation illustrating important aspects of the scientific method.
Introductory Applied Statistics I: One and Two Sample Statistics and Simple Regression
This material covers biostatistcal methods commonly used to quantify outcomes in a single group or to compare outcomes across groups identified by a single additional variable (covariate). The materials presented here were primarily developed when Professor Emerson taught the graduate courses Biost 517: Applied Biostatistics I (for graduate students in public health disciplines other than biostatistics) and Biost 514: Biostatistics I (for first year graduate students majoring in biostatistics). The materials thus correspond roughly to a 4 credit hour course taught over a 13 week quarter. Although they were graded separately, the two courses were taught conjointly, with the goal of exposing both audiences to the interdisciplinary collaborative environment that is prevalent in biomedical research.
Introductory Applied Statistics II: Multiple Regression
This material covers biostatistcal methods commonly used to compare across groups defined by two or more covariates. outcomes in a single group or to compare outcomes across two groups. As such, the course covers linear regression, logistic regression, Poisson regression, and proportional hazards regression. The materials presented here were primarily developed when Professor Emerson taught the graduate courses Biost 518: Applied Biostatistics II (for graduate students in public health disciplines other than biostatistics) and Biost 514: Biostatistics II (for first year graduate students majoring in biostatistics). The materials thus correspond roughly to a 4 credit hour course taught over a 13 week quarter. Although they were graded separately, the two courses were taught conjointly, with the goal of exposing both audiences to the interdisciplinary collaborative environment that is prevalent in biomedical research. Some material in survival analysis and categorical data analysis from more advanced courses is included and clearly marked as such.
Mathematical Statistics
This material covers statistical theory at a level appropriate for first year graduate students. The materials presented here were primarily developed when Professor Emerson taught the graduate courses Stat 512 and Stat 513: Statistical Inference to first year graduate students in statistics and biostatistics. The materials thus correspond to a two quarter sequence of 4 credit hour courses each quarter.
Theory of Linear Models
This material covers the statistical theory behind the linear regression model and its extensions to the generalized linear model and estimating equations. The materials presented here were primarily developed when Professor Emerson taught the graduate course Biost 533: Theory of Linear Models to first year graduate students in biostatistics. at a level appropriate for first year graduate students. The materials presented here were primarily developed when Professor Emerson taught the graduate courses Stat 512 and Stat 513: Statistical Inference to first year graduate students in statistics and biostatistics. The materials thus correspond to a one quarter 3 credit hour course.