Emerson Statistics - Introductory Applied Biostatistics

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Scott S. Emerson, M.D., Ph.D.
Professor of Biostatistics
Department of Biostatistics
University of Washington

Online: Introductory Applied Biostatistics
This course provides an introduction to the statistical analysis of data.

The major objectives of this course are to explore the ways in which statistical methods can be used to address scientific questions, to present simple data analysis methods, and to teach a general approach to a data analysis problem. To those ends, this course will stress the general abstraction of descriptive and inferential statistics to address a scientific question. We primarily address methods for the setting of one response variable and one grouping variable. This includes one and two sample problems, one way analysis of variance, and simple regression. Late in the course we address stratified analyses.

Topics covered will include definition of common descriptive techniques, estimation and testing for continuous, discrete, and censored response variables in parametric models, and semiparametric and nonparametric alternatives to those tests, including Monte Carlo methods. Emphasis will be placed on the similarity among the various forms of analyses.

The materials for this course are primarily re-packaging of the handouts and lectures from Biost 514 / 517 at the University of Washington, especially as taught in fall 2012.

Tutorial on Viewing Video Courses (mp4)
Detailed Syllabus (pdf)
Supplementary Materials (including R)
Lectures Handouts Video Homework Reading
L01: Overview 4/pg   1/pg 16:16 HW #01
(Key   R   Stata)
Detailed Syllabus
L02: Five Questions Answered with Statistics 4/pg   1/pg
    A: Scientific setting Slides 01 - 06 05:11    
    B: General classification Slides 07 - 08 07:41    
    C: Q1: Clustering cases Slides 09 - 11 05:13    
    D: Q2: Clustering variables Slides 12 - 15 07:17    
    E: Q3: Quantifying distributions Slides 16 - 20 08:11    
    F: Q4a: Hypothesizing associations Slides 21 - 26 08:31    
    G: Q4b: Detecting associations Slides 27 - 32 22:40    
    H: Q4c: Subgroups / Effect modification Slides 33 - 36 20:56    
    I: Q5: Prediction Slides 37 - 45 13:34    
    J: Statistical Tasks Slides 46 - 52 10:55    
L03: Overview of Descriptive Statistics 4/pg   1/pg
    A: Purpose; Errors, Materials Slides 01 - 07 09:48    
    B: Purpose: Validity of Assumptions Slides 08 - 14 20:29    
    C: Sampling Scheme Slides 15 - 25 16:43    
    D: Association Slides 26 - 32 12:17   Reporting Associations: sec 1-2
    E: Classifying Variables; Binary Slides 33 - 40 08:06    
    F: Categorical; Quantitative Slides 41 - 48 09:41    
    G: Censored Variables Slides 49 - 50 03:45    
    H: Types of Summary Measures Slides 51 - 66 04:55    

Possible reference texts (I use no text, because none seems sufficiently distribution-free in focus)

R  Rosner B: Fundamentals of Biostatistics, 5th ed.
PG  Pagano, Gauvreau: Principles of Biostatistics
FvBHL  Fisher, van Belle, Heagerty, Lumley: Biostatistics: A Methodology for the Health Sciences, 2nd ed.
F  Fleiss J: Statistical Methods for Rates and Proportions
KK  Kleinbaum, Klein: Survival Analysis: A Self-Learning Text
PM  Parmar MKB, Machin D: Survival Analysis: A Practical Approach
KM  Klein JP, Moeschberger ML: Survival Analysis: Techniques for Censored and Truncated Data