## April 2014 |

04 | Friday | R Programming - Intermediate | | (4 weeks) |

| | R for Statistical Analysis | | (4 weeks) |

| | Generalized Linear Models | | (4 weeks) |

| | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Introductory Statistics for Credit | | (9 weeks) |

| | Meta Analysis | | (4 weeks) |

11 | Friday | Statistics 2 – Inference and Association | | (4 weeks) |

| | Discrete Choice Modeling and Conjoint Analysis | | (4 weeks) |

| | Introduction to Quantitative Risk Analysis | | (4 weeks) |

| | R Programming - Introduction 2 | | (4 weeks) |

| | Data Mining: Unsupervised Techniques | | (4 weeks) |

18 | Friday | Statistical Analysis of Microarray Data with R | | (4 weeks) |

| | Survey of Statistics for Beginners | | (3 weeks) |

25 | Friday | Advanced Logistic Regression | | (4 weeks) |

| | Bayesian Regression Modeling via MCMC Techniques | | (4 weeks) |

| | Interactive Data Visualization | | (4 weeks) |

| | Applied Predictive Analytics, in partnership with CrowdANALYTIX | | (4 weeks) |

## May 2014 |

02 | Friday | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Graphics in R | | (4 weeks) |

| | Introductory Statistics for Credit | | (9 weeks) |

09 | Friday | Mixed and Hierarchical Linear Models | | (4 weeks) |

| | Spatial Statistics with Geographic Information Systems | | (4 weeks) |

| | Statistics 2 – Inference and Association | | (4 weeks) |

| | R Programming - Introduction 1 | | (4 weeks) |

16 | Friday | Statistics 3 – ANOVA and Regression | | (3 weeks) |

| | Financial Risk Modeling | | (4 weeks) |

| | Introduction to Structural Equation Modeling | | (4 weeks) |

| | Regression Analysis | | (4 weeks) |

| | Sample Size and Power Determination | | (4 weeks) |

23 | Friday | Principal Components and Factor Analysis | | (4 weeks) |

| | Introduction to Bayesian Hierarchical and Multi-level Models | | (4 weeks) |

| | Biostatistics in R: Clinical Trial Applications | | (4 weeks) |

| | Modeling Count Data | | (4 weeks) |

| | R Programming - Advanced | | (4 weeks) |

30 | Friday | Prediction & Tolerance Intervals; Measurement and Reliability | | (4 weeks) |

| | Practical Rasch Measurement - Core Topics | | (4 weeks) |

| | Advanced Analytics and Machine Learning with Hadoop | | (4 weeks) |

## June 2014 |

06 | Friday | Statistics 2 – Inference and Association | | (4 weeks) |

| | Text Mining | | (4 weeks) |

| | Introduction to Statistics 1 AP: Inference for a Single Variable | | (3 weeks) |

| | Calculus Review | | (3 weeks) |

| | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Introductory Statistics for Credit | | (9 weeks) |

13 | Friday | Logistic Regression | | (4 weeks) |

| | R Programming - Introduction 2 | | (4 weeks) |

| | Introduction to Statistical Modeling | | (4 weeks) |

20 | Friday | Introduction to Smoothing and P-spline Techniques using R | | (4 weeks) |

| | Introduction to Statistical Issues in Clinical Trials | | (4 weeks) |

| | Probability Distributions | | (4 weeks) |

27 | Friday | Matrix Algebra Review | | (4 weeks) |

| | Data Mining - R | | (4 weeks) |

| | Advanced Structural Equation Modeling | | (4 weeks) |

## July 2014 |

04 | Friday | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Practical Rasch Measurement - Further Topics | | (4 weeks) |

| | Introduction to Resampling Methods | | (3 weeks) |

| | Introduction to Bayesian Statistics | | (4 weeks) |

| | Introductory Statistics for Credit | | (9 weeks) |

11 | Friday | Statistics 3 – ANOVA and Regression | | (3 weeks) |

| | Introduction to Statistics 2 AP: Working with Bivariate Data | | (3 weeks) |

| | Multivariate Statistics | | (3 weeks) |

| | Survey Design and Sampling Procedures | | (4 weeks) |

| | Statistics 2 – Inference and Association | | (4 weeks) |

18 | Friday | Modeling Longitudinal and Panel Data | | (4 weeks) |

| | Natural Language Processing | | (4 weeks) |

| | Predictive Analytics 1 - Machine Learning Tools | | (4 weeks) |

25 | Friday | Clinical Trials - Phamacokinetics and Bioequivalence | | (4 weeks) |

| | R for Statistical Analysis | | (4 weeks) |

| | Visualization in R with ggplot2 | | (4 weeks) |

| | Meta Analysis | | (4 weeks) |

## August 2014 |

01 | Friday | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Introductory Statistics for Credit | | (9 weeks) |

| | R Programming - Introduction 1 | | (4 weeks) |

| | SQL and R - Introduction to Database Queries | | (4 weeks) |

| | Maximum Likelihood Estimation | | (2 weeks) |

08 | Friday | Statistics 2 – Inference and Association | | (4 weeks) |

| | Many-Facet Rasch Measurement | | (4 weeks) |

| | Biostatistics 1 | | (4 weeks) |

| | Biostatistics for Credit | | (9 weeks) |

15 | Friday | Survey Analysis | | (4 weeks) |

| | Introduction to Python for Analytics | | (4 weeks) |

| | Introduction to Social Network Analysis (SNA) | | (4 weeks) |

22 | Friday | Introduction to Optimization | | (4 weeks) |

| | Modeling in R | | (4 weeks) |

| | Predictive Analytics 2 - Neural Nets and Regression | | (4 weeks) |

| | Introduction to Item Response Theory (IRT) | | (4 weeks) |

29 | Friday | Meta Analysis 2 | | (4 weeks) |

| | Sentiment Analysis | | (4 weeks) |

| | Introduction to Bayesian Computing and Techniques | | (4 weeks) |

| | Political Analytics | | (4 weeks) |

## September 2014 |

05 | Friday | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Logistic Regression | | (4 weeks) |

| | Statistics 2 – Inference and Association | | (4 weeks) |

| | Introductory Statistics for Credit | | (9 weeks) |

| | R Programming - Introduction 2 | | (4 weeks) |

12 | Friday | Statistics 3 – ANOVA and Regression | | (3 weeks) |

| | Rasch Applications, Part 1: How to Construct a Rasch Scale | | (6 weeks) |

| | Introduction to Quantitative Risk Analysis | | (4 weeks) |

| | Biostatistics 2 | | (4 weeks) |

| | Forecasting Analytics | | (4 weeks) |

19 | Friday | Survival Analysis | | (4 weeks) |

| | Bootstrap Methods | | (4 weeks) |

| | Mapping in R | | (4 weeks) |

26 | Friday | Advanced Optimization | | (4 weeks) |

| | Bayesian Statistics in R | | (4 weeks) |

| | Categorical Data Analysis | | (4 weeks) |

| | R Programming - Intermediate | | (4 weeks) |

| | Applied Predictive Analytics, in partnership with CrowdANALYTIX | | (4 weeks) |

## October 2014 |

03 | Friday | Missing Data | | (4 weeks) |

| | Regression Analysis | | (4 weeks) |

| | R for Statistical Analysis | | (4 weeks) |

| | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Introductory Statistics for Credit | | (10 weeks) |

10 | Friday | Statistics 2 – Inference and Association | | (4 weeks) |

| | Analysis of Survey Data from Complex Sample Designs | | (4 weeks) |

| | Graphics in R | | (4 weeks) |

| | Calculus Review | | (3 weeks) |

17 | Friday | Data Mining: Unsupervised Techniques | | (4 weeks) |

| | Practical Rasch Measurement - Core Topics | | (4 weeks) |

24 | Friday | Safety Monitoring Committees in Clinical Trials | | (4 weeks) |

| | Bayesian Regression Modeling via MCMC Techniques | | (4 weeks) |

31 | Friday | Cluster Analysis | | (4 weeks) |

| | Modeling Count Data | | (4 weeks) |

| | Introduction to Analytics using Hadoop | | (4 weeks) |

| | Rasch Applications, Part 2: Clinical Assessment, Survey Research, and Educational Measurement | | (4 weeks) |

| | Interactive Data Visualization | | (4 weeks) |

## November 2014 |

07 | Friday | Statistics 1 - Probability and Study Design | | (4 weeks) |

| | Categorical Data - Applied Modeling | | (4 weeks) |

| | Spatial Statistics with Geographic Information Systems | | (4 weeks) |

| | Introduction to Structural Equation Modeling | | (4 weeks) |

| | Advanced Survival Analysis | | (4 weeks) |

| | Introductory Statistics for Credit | | (10 weeks) |

| | R Programming - Introduction 1 | | (4 weeks) |

14 | Friday | Statistics 3 – ANOVA and Regression | | (3 weeks) |

| | Epidemiologic Statistics | | (5 weeks) |

| | Matrix Algebra Review | | (4 weeks) |

| | Statistics 2 – Inference and Association | | (4 weeks) |

21 | Friday | Risk Simulation and Queuing | | (4 weeks) |

| | Introduction to Bayesian Hierarchical and Multi-level Models | | (4 weeks) |

| | Survey of Statistics for Beginners | | (3 weeks) |

28 | Friday | Meta Analysis | | (6 weeks) |

| | Maximum Likelihood Estimation | | (1 weeks) |

## December 2014 |

05 | Friday | Statistics 1 - Probability and Study Design | | (5 weeks) |

| | Introductory Statistics for Credit | | (9 weeks) |

12 | Friday | Statistics 2 – Inference and Association | | (5 weeks) |

| | Introduction to Statistical Issues in Clinical Trials | | (5 weeks) |

| | Spatial Analysis Techniques in R | | (3 weeks) |