STATISTICAL ANALYSTS

Statistical Analysts are statisticians and data miners who deploy a wide range of sophisticated techniques to create models, forecasts and analyses. Statistical Analysts use tools including SAS/STAT, SAS/ETS, SAS Enterprise Guide 4 and SAS Enterprise Miner.

Advanced and Specialty Courses:

• Data Mining Techniques: Theory and Practice
• Multivariate Statistical Methods: Practical Research Applications
• JMP Software: Analysis of Attribute Data

Statistics I: Introduction to ANOVA, Regression, and Logistic Regression

This course teaches SAS users how to generate analyses using either continuous or categorical response (dependent) variables.

Learn how to:

• generate descriptive statistics and explore data with graphs
• perform analysis of variance and apply multiple comparison techniques
• perform linear regression and assess the assumptions
• identify potential outliers in multiple regression
• detect associations among categorical variables
• fit a multiple logistic regression model.

Who should attend: Statisticians, researchers, and business analysts who use SAS programming to analyze data

Level II: Fundamentals

Duration: 3 days
Learn more: support.sas.com/courses/stat1.html

Statistics II: ANOVA and Regression

This course teaches you how to analyze continuous response data and discrete count data. Linear regression, Poisson regression, Gamma regression, analysis of variance, and mixed models ANOVA are presented in the course.

Learn how to:

• use PROC REG to fit polynomial regression models
• perform model diagnostics and remedial measures using a variety of procedures
• fit a Poisson and gamma regression model using the GENMOD procedure
• perform analysis of variance and fit ANCOVA models using the GLM procedure
• fit regression models with dummy variables
• fit ANOVA models with random effects using the MIXED procedure.

Who should attend: Statisticians, business analysts, data analysts, and researchers with some statistical training

Level III: Intermediate

Duration: 3 days

Learn more: support.sas.com/courses/stat2.html

Predictive Modeling Using Logistic Regression

This course covers predictive modeling using SAS/STAT® software with emphasis on the LOGISTIC procedure. This course also discusses selecting variables, assessing models, treating missing values, and using efficiency techniques for massive data sets.

Learn how to:

• use logistic regression to model an individual’s behavior as a function of known inputs
• handle missing data values
• tackle multicollinearity in your predictors
• assess model performance and compare models.

Who should attend: Modelers, analysts, and statisticians who need to build predictive models, particularly models from the banking, financial services, direct marketing, insurance, and telecommunications industries

Level IV: Advanced

Duration: 2 days

Learn more: support.sas.com/courses/pmlr.html

Mixed Models Analyses Using the SAS® System

This course teaches you how to analyze linear and generalized mixed models using the MIXED and GLIMMIX procedures, respectively.

Learn how to:
analyze data (including binary data) with random effects
fit random coefficient models and hierarchical linear models
analyze repeated measures data
obtain and interpret the best linear unbiased predictions
deal with convergence issues.

Who should attend: Statisticians, experienced data analysts, and researchers with sound statistical knowledge

Level IV: Advanced

Duration: 3 days

Learn more: support.sas.com/courses/aglm.html

JMP® Software: Statistical Data Exploration

This course is designed as an important first step for those who want to use JMP 7 to manage and analyze data.

Learn how to:
navigate the JMP interface
manage data effectively in JMP
use the extensive graphical capabilities in JMP to explore data
create reports in JMP.

Who should attend: Anyone who wants to use JMP 7 to manage and analyze data

Level II: Fundamentals

Duration: 1 day

Learn more: support.sas.com/courses/jdex7.html

JMP® Software: ANOVA and Regression

This course teaches how to analyze data with a single continuous response variable using analysis of variance and regression methods in JMP 7. You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals are also introduced.

Learn how to use JMP software to:
perform a t-test
generate and interpret an analysis of variance
create and interpret simple and multiple linear regression models
perform an ANCOVA
evaluate assumptions in statistical
hypothesis testing.

Who should attend: Analysts and researchers with some statistical training

Level III: Intermediate

Duration: 2 days

Learn more: support.sas.com/courses/janr7.html