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Course Calendar

Year 2012

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February 2012

03 Friday Introduction to Statistics 1: Sampling and Inference (3 weeks)
Introduction to Statistics 3 - ANOVA and Multiple Regression (3 weeks)
10 Friday Introduction to R - Data Handling (4 weeks)
17 Friday Introduction to Design of Experiments (4 weeks)
Introduction to Resampling Methods (3 weeks)
Multivariate Statistics (4 weeks)
24 Friday Matrix Algebra Review (4 weeks)
Ecological and Environmental Sampling (4 weeks)
Introduction to Bayesian Statistics (4 weeks)

March 2012

02 Friday Introduction to Statistics for Beginners (3 weeks)
Introduction to Statistics 2: Inference and Relationships (3 weeks)
09 Friday Introduction to Data Mining (4 weeks)
Modeling in R (4 weeks)
Biostatistics 2 (4 weeks)
Introduction to Bayesian Computing and Techniques (4 weeks)
16 Friday Advanced Statistical Process Control (3 weeks)
Bootstrap Methods (4 weeks)
Logistic Regression (4 weeks)
23 Friday Bayesian Environmental Statistics (4 weeks)
Adaptive Designs for Clinical Trials (4 weeks)
Survival Analysis (4 weeks)
Survey Analysis in R (4 weeks)
30 Friday Maximum Likelihood Estimation (2 weeks)
Forecasting (4 weeks)
Categorical Data Analysis (4 weeks)
Regression Analysis (4 weeks)

April 2012

06 Friday Introduction to Statistics 1: Sampling and Inference (3 weeks)
Introduction to Statistics 3 - ANOVA and Multiple Regression (3 weeks)
Generalized Linear Models (4 weeks)
Meta Analysis (4 weeks)
13 Friday Discrete Choice Modeling and Conjoint Analysis (4 weeks)
Advanced Design of Experiments (4 weeks)
Introduction to Quantitative Risk Analysis (4 weeks)
Programming in R (4 weeks)
20 Friday Acceptance Sampling for Quality Control (4 weeks)
Survey of Statistics for Beginners (3 weeks)
Statistical Analysis of Microarray Data with R (4 weeks)
27 Friday Interactive Data Visualization (4 weeks)
Advanced Logistic Regression (4 weeks)
Bayesian Regression Modeling via MCMC Techniques (4 weeks)

May 2012

04 Friday Introduction to Statistics for Beginners (3 weeks)
Introduction to Statistics 2: Inference and Relationships (3 weeks)
11 Friday Mixed and Hierarchical Linear Models (4 weeks)
Spatial Statistics with Geographic Information Systems (4 weeks)
Graphics in R (4 weeks)
Modeling Count Data (4 weeks)
18 Friday Introduction to Structural Equation Modeling (4 weeks)
Advanced Survival Analysis (4 weeks)
Sample Size and Power Determination (4 weeks)
Introduction to R - Statistical Analysis (4 weeks)
Financial Risk Modeling (4 weeks)
25 Friday Principal Components and Factor Analysis (4 weeks)
Engineering Statistics (4 weeks)
Biostatistics in R: Clinical Trial Applications (4 weeks)
Calculus Review (3 weeks)

June 2012

01 Friday Introduction to Statistics 1: Sampling and Inference (3 weeks)
Introduction to Statistics 3 - ANOVA and Multiple Regression (3 weeks)
Epi 1: Fundamentals of Epidemiology (5 weeks)
08 Friday Text Mining (4 weeks)
Introduction to Statistics 1 AP: Inference for a Single Variables (3 weeks)
15 Friday Programming in R - Advanced (4 weeks)
Introduction to Assessment/Measurement in Education (4 weeks)
Logistic Regression (4 weeks)
22 Friday Introduction to Statistical Issues in Clinical Trials (4 weeks)
Probability Distributions (4 weeks)
Smoothing with P-splines (Using R) (4 weeks)
An Introduction to Bayesian Hierarchical and Multi-level Models (4 weeks)
29 Friday Matrix Algebra Review (4 weeks)
Data Mining - R (4 weeks)
Advanced Structural Equation Modeling (4 weeks)

July 2012

06 Friday Introduction to Resampling Methods (3 weeks)
13 Friday Survey Design and Sampling Procedures (4 weeks)
Multivariate Statistics (4 weeks)
Introduction to Statistics 2 AP: Working with Bivariate Data (3 weeks)
20 Friday Sentiment Analysis (3 weeks)
Visualization in R with ggplot2 (4 weeks)
Modeling Longitudinal and Panel Data (4 weeks)
Meta Analysis (4 weeks)
27 Friday Clinical Trials - Phamacokinetics and Bioequivalence (4 weeks)
Introduction to R - Data Handling (4 weeks)

August 2012

03 Friday Maximum Likelihood Estimation (2 weeks)
10 Friday Sample Size using PASS software from NCSS (4 weeks)
Biostatistics 1 (4 weeks)
17 Friday Survey Analysis (4 weeks)
Introduction to Bayesian Statistics (4 weeks)
24 Friday Introduction to Optimization (4 weeks)
31 Friday Epi 2: Bias in Epidemiologic Studies (4 weeks)
Meta Analysis 2 (4 weeks)
Modeling in R (4 weeks)
Natural Language Processing (4 weeks)

September 2012

07 Friday Calculus Review (4 weeks)
Introduction to Data Mining (4 weeks)
Logistic Regression (4 weeks)
14 Friday Biostatistics 2 (4 weeks)
Forecasting (4 weeks)
National Income Statistics (3 weeks)
Rasch Applications in Clinical Assessment, Survey Research, and Educational Measurement (4 weeks)
Avoiding Selection Bias in Randomized Clinical Trials (5 weeks)
21 Friday Survival Analysis (4 weeks)
Introduction to Bayesian Computing and Techniques (4 weeks)
28 Friday Categorical Data Analysis (4 weeks)
Regression Analysis (4 weeks)
Introduction to R - Statistical Analysis (4 weeks)
Advanced Optimization (4 weeks)

October 2012

12 Friday Data Mining: Unsupervised Techniques (4 weeks)
Environmental Statistics (4 weeks)
Data Mining Mistakes and How to Avoid Them (2 weeks)
19 Friday Statistical Analysis of Microarray Data with R (4 weeks)
Graphics in R (4 weeks)
Modeling Count Data (4 weeks)
Clinical Trials - Clustering (4 weeks)
26 Friday Programming in R (4 weeks)
Interactive Data Visualization (4 weeks)
Safety Monitoring Committees in Clinical Trials (4 weeks)

November 2012

02 Friday Matrix Algebra Review (4 weeks)
Cluster Analysis (4 weeks)
09 Friday Advanced Survival Analysis (4 weeks)
Spatial Statistics with Geographic Information Systems (4 weeks)
Introduction to Structural Equation Modeling (4 weeks)
Categorical Data - Applied Modeling (4 weeks)
16 Friday Biostatistics in R: Clinical Trial Applications (4 weeks)
Bayesian Regression Modeling via MCMC Techniques (4 weeks)
Introduction to Support Vector Machines in R (4 weeks)
23 Friday Sample Size and Power Determination (5 weeks)
Survey of Statistics for Beginners (3 weeks)
Risk Simulation and Queuing (4 weeks)
Generalized Linear Models (5 weeks)
Risk Simulation and Queuing (4 weeks)
30 Friday Meta Analysis (5 weeks)

December 2012

07 Friday Smoothing with P-splines (Using R) (5 weeks)
Maximum Likelihood Estimation (2 weeks)
14 Friday Spatial Analysis Techniques in R (5 weeks)

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