DSML

A Primer on Missing Data Methods for Data Scientists

Speaker

Heather Harris

Details

Missing data is a common nuisance data scientists must deal with when building models, and how missing data are accounted for can impact model accuracy and efficiency. Often one of the biggest gaps between theory and practice is how to approach missing data, and understanding what it means for your results.

This talk will be a primer on missing data mechanisms, data screening steps, and an introduction to common imputation methods.

Event type:

Speaker Series

Preparation:

None

April 12, 2023

8:00 pm

-

9:00 pm

April 12, 2023

Online

Zoom

While this event is FREE, tickets are required & space is limited!

Attend this event

About the speaker

Heather Harris

Data Scientist

Heather has a PhD in statistics related to cognitive processes, and she has worked as a consulting data scientist and statistician for 4 years. As a consultant, she’s led a multitude of diverse projects including predicting audiences for the first movie with a theatrical release following the pandemic, predicting and segmenting viewers for several television shows and networks, developing scoring algorithms for EdTech companies, and working with clients from several substantive areas to architect data ecosystems for advanced analytics. She is passionate about teaching best statistical practices and communicating complex results to non-technical audiences. When she's not crunching numbers, you can find her exploring museums in DC and playing Euchre with friends.