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COURSE CALENDAR

October 2009
   2 Friday Categorical Data Analysis 1 (4 weeks)
    Regression Analysis (4 weeks)
    Introduction to Quantitative Risk Analysis (4 weeks)
    Calculus Review (2 weeks)
   9 Friday Epi 3: Analysis of Epidemiologic Data (4 weeks)
    Introduction to Statistics 3 - ANOVA and Multiple Regression (3 weeks)
    Maximum Likelihood Estimation (2 weeks)
    Introduction to Statistics 1: Inference for a Single Variable (3 weeks)
   16 Friday Data Mining: Unsupervised Techniques (4 weeks)
    Environmental Statistics (4 weeks)
    Engineering Statistics (4 weeks)
   23 Friday Modeling Count Data (4 weeks)
    Many-Facet Rasch Measurement (4 weeks)
    Statistical Analysis of Microarray Data with R (5 weeks)
    Forecasting - Advanced (4 weeks)
    Introduction to Bayesian Statistics (4 weeks)
   30 Friday Financial Risk Modeling (4 weeks)
    Advanced Logistic Regression (4 weeks)
    Introduction to R - Statistical Analysis (4 weeks)
    Introduction to Statistical Issues in Clinical Trials (4 weeks)
November 2009
   6 Friday Cluster Analysis (4 weeks)
    Graphics in R (4 weeks)
    Introduction to Statistics for Beginners (3 weeks)
    Introduction to Statistics 2: Working with Bivariate Data (3 weeks)
   13 Friday Introduction to Structural Equation Modeling (4 weeks)
    Categorical Data Analysis 2 (4 weeks)
    Probability Distributions (4 weeks)
   20 Friday Missing Data Analysis (4 weeks)
    Bayesian Approaches to Clinical Trials (4 weeks)
    Introduction to Support Vector Machines in R (4 weeks)
    Visualization (4 weeks)
   27 Friday Survey of Statistics for Beginners (3 weeks)
    Generalized Linear Models (4 weeks)
    Sample Size and Power Determination (4 weeks)
December 2009
   4 Friday Meta Analysis (4 weeks)
    Introduction to Statistics 3 - ANOVA and Multiple Regression (3 weeks)
    Introduction to Statistics 1: Inference for a Single Variable (3 weeks)
   11 Friday Matrix Algebra Review (2 weeks)
   18 Friday Maximum Likelihood Estimation (2 weeks)
January 2010
   8 Friday Practical Rasch Measurement - Core Topics (4 weeks)
    Introduction to Statistics 2: Working with Bivariate Data (3 weeks)
    Introduction to Statistics for Beginners (3 weeks)
   15 Friday Statistical Process Control (4 weeks)
    Introduction to R - Statistical Analysis (4 weeks)
    Advanced Structural Equation Modeling (4 weeks)
   22 Friday Decision Trees and Rule-Based Segmentation (4 weeks)
   29 Friday Biostatistics 1 (4 weeks)
February 2010
   5 Friday Nonparametric Statistics (4 weeks)
    Introduction to Statistics 3 - ANOVA and Multiple Regression (3 weeks)
    Clinical Trial Safety Monitoring (4 weeks)
   12 Friday Modeling in R (4 weeks)
    Clinical Trials - Practicum 1 (4 weeks)
   19 Friday Multivariate Statistics (4 weeks)
    Introduction to Design of Experiments (4 weeks)
   26 Friday Ecological and Environmental Sampling (4 weeks)
    Introduction to Resampling Methods (3 weeks)
    Introduction to Bayesian Statistics (4 weeks)
March 2010
   5 Friday Introduction to R - Data Handling (4 weeks)
    Practical Rasch Measurement - Further Topics (4 weeks)
    Introduction to Data Mining (4 weeks)
   12 Friday Logistic Regression (4 weeks)
    Biostatistics 2 (4 weeks)
    Introductory Bayesian Modeling via MCMC Techniques (4 weeks)
   19 Friday Bootstrap Methods (4 weeks)
   26 Friday Bayesian Environmental Statistics (4 weeks)
    Forecasting (4 weeks)
    Survival Analysis (4 weeks)
    Clinical Trials-Practicum 2 (Drug Trials) (4 weeks)
April 2010
   9 Friday Advanced Design of Experiments (4 weeks)
    Discrete Choice Modeling and Conjoint Analysis (4 weeks)
    Meta Analysis (4 weeks)
    Categorical Data Analysis 1 (4 weeks)
    Introduction to Quantitative Risk Analysis (4 weeks)
   16 Friday Adaptive Designs for Clinical Trials (4 weeks)
   23 Friday Regression Analysis (4 weeks)
    Statistical Analysis of Microarray Data with R (5 weeks)
    Graphics in R (4 weeks)
   24 Saturday Randomization, Permutation and Exact Tests (4 weeks)
   30 Friday Practical Rasch Measurement - Core Topics (4 weeks)
May 2010
   7 Friday Mixed and Hierarchical Linear Models (4 weeks)
   14 Friday Spatial Statistics With Geographic Information Systems (4 weeks)
    Categorical Data Analysis 2 (4 weeks)
    Sample Size and Power Determination (4 weeks)
    Introduction to Structural Equation Modeling (4 weeks)
   21 Friday Introduction to R - Statistical Analysis (4 weeks)
   28 Friday Engineering Statistics (4 weeks)
    Probability Distributions (4 weeks)
June 2010
   4 Friday Epi 1: Fundamentals of Epidemiology (5 weeks)
   11 Friday Introduction to Statistics 1-AP: Inference for a Single Variable (3 weeks)
   18 Friday Text Mining (4 weeks)
    Introduction to Assessment/Measurement in Education (4 weeks)
   25 Friday Many-Facet Rasch Measurement (4 weeks)
    Advanced Structural Equation Modeling (4 weeks)
    Introduction to Statistical Issues in Clinical Trials (4 weeks)
July 2010
   2 Friday Modeling Longitudinal and Panel Data (4 weeks)
    Introduction to Resampling Methods (3 weeks)
   9 Friday Introduction to Statistics 2 AP: Working with Bivariate Data (3 weeks)
    Survey Design and Sampling Procedures (4 weeks)
August 2010
   6 Friday Biostatistics 1 (4 weeks)
   13 Friday Survey Analysis (4 weeks)
   20 Friday Practical Rasch Measurement - Core Topics (4 weeks)
    Natural Language Processing (4 weeks)
   28 Saturday Nonparametric Statistics (4 weeks)
September 2010
   3 Friday Epi 2: Designing Epidemiologic Studies (4 weeks)
   10 Friday Forecasting (4 weeks)
    Introduction to Data Mining (4 weeks)
    Logistic Regression (4 weeks)
    Introductory Bayesian Modeling via MCMC Techniques (4 weeks)
   17 Friday Avoiding Selection Bias in Randomized Clinical Trials (5 weeks)
    Rasch Applications in Clinical Assessment, Survey Research, and Educational Measurement (4 weeks)
    Introduction to R - Data Handling (4 weeks)
   24 Friday Bootstrap Methods (4 weeks)
    Survival Analysis (4 weeks)
    National Income Statistics (3 weeks)
October 2010
   1 Friday Introduction to Bayesian Statistics (4 weeks)
    Categorical Data Analysis 1 (4 weeks)
    Introduction to Quantitative Risk Analysis (4 weeks)
   8 Friday Epi 3: Analysis of Epidemiologic Data (4 weeks)
    Regression Analysis (4 weeks)
   15 Friday Data Mining: Unsupervised Techniques (4 weeks)
    Environmental Statistics (4 weeks)
   22 Friday Practical Rasch Measurement - Further Topics (4 weeks)
    Modeling in R (4 weeks)
    Statistical Analysis of Microarray Data with R (5 weeks)
    Forecasting - Advanced (4 weeks)
    Modeling Count Data (4 weeks)
November 2010
   5 Friday Cluster Analysis (4 weeks)
    Graphics in R (4 weeks)
   12 Friday Categorical Data Analysis 2 (4 weeks)
   19 Friday Bayesian Approaches to Clinical Trials (4 weeks)
December 2010
   17 Friday Spatial Statistics With Geographic Information Systems (4 weeks)

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