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SAS Studio

Kurstitel Stufe Kursformat
User-Friendly, Comprehensive SAS® Statistical Applications: Multivariate Models Business Knowledge Series
In this course, you learn how to perform data preparation, exploration, and comprehensive multivariate statistical models such as principal component, exploratory factor, and cluster analyses using five user-friendly, precompiled SAS macro applications. This user-friendly approach integrates statistical and graphical analysis tools that are available in SAS/STAT and provides complete statistical solutions without writing SAS code or using a point-and-click approach. Step-by-step instructions show how to use these applications and how to interpret the results. After class, you can download the compiled macro catalog to perform comprehensive analysis on your own projects.

3 Für Fortgeschrittene Classroom Live Web Classroom
User-Friendly, Comprehensive SAS® Statistical Applications: Classification Models Business Knowledge Series
In this course, you use six user-friendly, precompiled SAS macro applications to perform comprehensive canonical, parametric and nonparametric discriminant, and decision tree analyses. As part of these analyses, you prepare and explore data, select variables, and create diagnostic plots related to model specification and model assumption validation. This user-friendly approach integrates statistical and graphical analysis tools that are available in SAS/STAT and provides complete statistical solutions without writing SAS code or using a point-and-click approach. Step-by-step instructions show you how to use these SAS/STAT applications and how to interpret the results. After class, you can download the compiled SAS macro catalog to perform comprehensive analysis on your own projects.

3 Für Fortgeschrittene Classroom Live Web Classroom
User-Friendly, Comprehensive SAS® Statistical Applications: Regression Models Business Knowledge Series
In this course, you use six user-friendly, precompiled SAS macro applications to perform comprehensive multiple linear and binary logistic regression analyses. As part of these analyses, you prepare and explore data, select variables, and create diagnostic plots related to model specification and model assumption validation. This user-friendly approach integrates statistical and graphical analysis tools that are available in SAS/STAT and provides complete statistical solutions without writing SAS code or using a point-and-click approach. Step-by-step instructions show you how to use these user-friendly SAS/STAT applications and how to interpret the results. After class, you can download the compiled SAS macro catalog to perform comprehensive analysis on your own projects.

3 Für Fortgeschrittene Classroom Live Web Classroom
Essential Data Analysis Using SAS® Studio Tasks: A Point-and-Click Approach
In this course, you gain introductory knowledge into exploratory data analysis using SAS Studio tasks that execute the FREQ, MEANS, and UNIVARIATE procedures. The course focuses on the differences among these procedures as well as output interpretation. Introductory statistics terminology is also discussed.

2 Basiswissen Classroom Live Web Classroom
Exploring SAS® Studio for SAS® Programmers
This course provides an introduction to SAS Studio for experienced SAS programmers. SAS Studio is an interface that enables users to write and submit SAS programs and use snippets and tasks to generate SAS code.

The self-study e-learning includes:

  • Annotatable course notes in PDF format.
  • Virtual Lab time to practice.

3 Für Fortgeschrittene Classroom Live Web Classroom e-Learning
Programming for SAS® Viya®
This course is for users who need to modify existing Base SAS programs that will execute in SAS Viya. This course leverages the power of SAS Cloud Analytic Services (CAS) to access, manage, and manipulate in-memory tables. This course is not intended for beginning SAS software users.

3 Für Fortgeschrittene Classroom Live Web Classroom e-Learning
Time Series Modeling Essentials
This course discusses the fundamentals of modeling time series data. The course focuses on the applied use of the three main model types used to analyze univariate time series: exponential smoothing, autoregressive integrated moving average with exogenous variables (ARIMAX), and unobserved components (UCM).

The e-learning format of this course includes Virtual Lab time to practice.

3 Für Fortgeschrittene Classroom Live Web Classroom e-Learning