Stats for Data Science

In this talk, we will discuss some aspects of classical statistical inference that are used everyday to help guide decision making. Using a case study of running an experiment to inform website design, we discuss how to test which design is better and by how much, quantify our uncertainty about this conclusion, and decide how long we need to run the experiment in order to be confident in our results.


  • Tags: statistics, confidence interval, testing, statistics, probability distributions, sampling bias, r
When:

Saturday Oct 17th, 4:00pm to 5:15pm (CDT)

Presented By:

Darren Homrighausen

About the Speaker(s):

Dr. Homrighausen is an Associate Professor of Statistics at Texas A & M University. Prior to teaching, Dr. Homrighausen recieved a Ph.D and M.S in statistics from Carnegie Mellon University


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