On-Demand Webinar

The Data Scientist Learning Journey: Statistics You Need to Know for Data Science

This webinar series is designed for individuals who want to elevate their data science skills using SAS® and keep pace with the most innovative technology.

The Data Scientist Learning Journey

About the webinar

Data scientists do lots of different kinds of work with data, but one thing they all have in common is the use of mathematics to model patterns observed in the world.

These mathematical models derive heavily from the field of statistics!

In this webinar, our experts, Sharad Saxena and Cat Truxillo, will talk about the statistical concepts that you are most likely to encounter on a daily basis as a working data scientist.

Why attend?

  • Learn about the statistics behind your analyses, why they matter and how to make sense of them.
  • Discuss the commonality between statistical and data science terminology.
  • Hear how to test a hypothesis and why.
  • Discover statistical solutions to common data difficulties and modeling issues.
  • Understand descriptive and inferential statistics – and predictive versus explanatory models.

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About the Experts

Catherine Truxillo
Director of Analytical Education, SAS

Catherine Truxillo has written or co-written SAS training courses for advanced statistical methods, including: multivariate statistics, linear and generalized linear mixed models, multilevel models, structural equation models, imputation methods for missing data, statistical process control, design and analysis of experiments, and cluster analysis. She also teaches SAS courses using SAS/IML®, SAS® Enterprise Guide®, SAS® Enterprise Miner, SAS Forecast Studio and JMP® software.

Sharad Saxena
Principal Analytical Training Consultant, SAS

Dr. Sharad Saxena is a Principal Analytical Training Consultant based at the SAS R&D center in Pune, India. Working in the field of statistics and analytics since 2000, he provides education consulting in advanced analytics and machine learning around the globe. Saxena has more than 35 publications, including research papers in journals such as the Journal of Statistical Planning and Inference, Communications in Statistics – Theory and Methods, Statistica, Statistical Papers, and Vikalpa. He is also a co-author of Randomness and Optimal Estimation in Data Sampling.