Data Skeptic

This miniepisode discusses the technique called Cross Validation - a process by which one randomly divides up a dataset into numerous small partitions. Next, (typically) one is held out, and the rest are used to train some model. The hold out set can then be used to validate how good the model does at describing/predicting new data.

Direct download: MINI_Cross_Validation.mp3
Category:general -- posted at: 7:51am PDT

This episode features a discussion with statistics PhD student Zach Seeskin about a project he was involved in as part of the Eric and Wendy Schmidt Data Science for Social Good Summer Fellowship.  The project involved exploring the relationship (if any) between streetlight outages and crime in the City of Chicago.  We discuss how the data was accessed via the City of Chicago data portal, how the analysis was done, and what correlations were discovered in the data.  Won't you listen and hear what ws found? 

Direct download: Streetlight_Outage_and_Crime_Rate_Analysis_with_Zach_Seeskin.mp3
Category:general -- posted at: 6:00am PDT

This episode loosely explores the topic of Experimental Design including hypothesis testing, the importance of statistical tests, and an everyday and business example.

Direct download: MINI_Experimental_Design.mp3
Category:miniepisode -- posted at: 6:00am PDT

In this week's episode, we discuss applied solutions to big data problem with big data engineer Jay Shankar.  The episode explores approaches and design philosophy to solving real world big data business problems, and the exploration of the wide array of tools available.

 

Direct download: Data_Skeptic_Podcast_-_Big_Data_Tools.mp3
Category:general -- posted at: 6:00am PDT

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