Data Skeptic

In this week's mini episode, Linhda and Kyle discuss Ant Colony Optimization - a numerical / stochastic optimization technique which models its search after the process ants employ in using random walks to find a goal (food) and then leaving a pheremone trail in their walk back to the nest. We even find some way of relating the city of San Francisco and running a restaurant into the discussion.

Our guest this week is Shahid Shah. Shahid is CEO at Netspective, and writes three blogs: Health Care Guy, Shahid Shah, and HitSphere - the Healthcare IT Supersite. During the program, Kyle recommended a talk from the 2014 MIT Sloan CIO Symposium entitled Transforming "Digital Silos" to "Digital Care Enterprise" which was hosted by our guest Shahid Shah. In addition to his work in Healthcare IT, he also the chairperson for Open Source Electronic Health Record Alliance, an non-profit organization that, amongst other activities, is hosting an upcoming conference. The 3rd annual OSEHRA Open Source Summit: Global Collaboration in Healthcare IT , which will be taking place September 3-5, 2014 in Washington DC. For our benevolent recommendation, Shahid suggested listeners may benefit from taking the time to read books on leadership for the insights they provide. For our self-serving recommendation, Shahid recommended listeners check out his company Netspective , if you are working with a company looking for help getting started building software utilizing next generation technologies.

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.

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 was found?

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

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.

In this minisode, we discuss Bayesian Updating - the process by which one can calculate the most likely hypothesis might be true given one's older / prior belief and all new evidence.

In the second full length episode of the podcast, we discuss the current state of personalized medicine and the advancements in genetics that have made it possible.

In this mini, we discuss p-values and their use in hypothesis testing, in the context of an hypothetical experiment on plant flowering, and end with a reference to the Particle Fever documentary and how statistical significance played a role.

A conversation with Convertro's Nathan Janos about methodologies used to help advertisers understand the affect each of their marketing efforts (print, SEM, display, skywriting, etc.) contributes to their overall return.