SAS Biostatistics​ Learning Subscription

Biostatistics

• COURSE

  Regression Methods Using SAS® Viya®

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  This course covers nine regression methods. The models include linear, logistic, quantile, generalized linear, generalized additive, mixed, survival, nonlinear, and partial least squares. The applications, strengths, and weaknesses of each method are discussed, along with how the methods are implemented in SAS Viya. A comparison of the SAS Viya procedures and SAS/STAT procedures for each method is also shown. Examples in the course show applications in banking, financial services, direct marketing, insurance, telecommunications, medical, and academic fields.
  
  The self-study e-learning includes:
  

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

  
  
  ENROLL

• COURSE

  Fitting Poisson Regression Models Using the GENMOD Procedure

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  This course is for those who analyze the number of occurrences of an event or the rate of occurrence of an event as a function of some predictor variables. For example, the rate of insurance claims, colony counts for bacteria or viruses, the number of equipment failures, and the incidence of disease can be modeled using Poisson regression models.
  
  This course includes practice data and exercises.
  
  ENROLL

• COURSE

  Survival Analysis Using the Proportional Hazards Model

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  This course discusses survival analysis concepts with an emphasis on health care problems. The course focuses on the Cox proportional hazards model, not the parametric models, and is not designed for predictive modelers.
  
  ENROLL

• COURSE

  Statistical Analysis with the GLIMMIX Procedure

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  This course focuses on the GLIMMIX procedure, a procedure for fitting generalized linear mixed models.
  
  ENROLL

• COURSE

  Programming with SAS/IML® Software

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  This course teaches you how to use the IML procedure via the programming language. You benefit from this course if you plan to use SAS/IML for manipulating matrices, simulating data, writing custom statistical analyses, or working with R. The programs in this course require SAS/IML 12.3 or later to run.
  
  The self-study e-learning includes:
  

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

  
  
  ENROLL

• COURSE

  SAS® Programming for R Users

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  This course is for experienced R users who want to apply their existing skills and extend them to the SAS environment. Emphasis is placed on programming and not statistical theory or interpretation. Students in this course should have knowledge of plotting, manipulating data, iterative processing, creating functions, applying functions, linear models, generalized linear models, mixed models, stepwise model selection, matrix algebra, and statistical simulations.
  
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• COURSE

  Responsible Innovation and Trustworthy AI

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  This course is designed for anyone who wants to gain a deeper understanding about the importance of trust and responsibility in AI, analytics, and innovation. The content is especially geared to those who are making business decisions based on machine learning and AI systems and those who are designing and training AI systems.
  
  Whether you are a programmer, an executive, an advisory board member, a tester, a manager, or an individual contributor, this course helps you gain foundational knowledge and skills to consider the issues related to responsible innovation and trustworthy AI. Empowered with the knowledge from this course, you can strive to find ways to design, develop, and use machine learning and AI systems more responsibly.
  
  We expect that each module can be completed in under an hour, and you can work at your own pace to complete the material. As we release new modules, you might lose progress through the material that you have completed, so please make a note of where you are leaving off before exiting the course.
  
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