11 min listen
NYC Speed Camera Analysis with Tim Schmeier
FromData Skeptic
ratings:
Length:
17 minutes
Released:
Feb 27, 2015
Format:
Podcast episode
Description
New York State approved the use of automated speed cameras within a specific range of schools. Tim Schmeier did an analysis of publically available data related to these cameras as part of a project at the NYC Data Science Academy. Tim's work leverages several open data sets to ask the questions: are the speed cameras succeeding in their intended purpose of increasing public safety near schools? What he found using open data may surprise you.
You can read Tim's write up titled Speed Cameras: Revenue or Public Safety? on the NYC Data Science Academy blog. His original write up, reproducible analysis, and figures are a great compliment to this episode.
For his benevolent recommendation, Tim suggests listeners visit Maddie's Fund - a data driven charity devoted to helping achieve and sustain a no-kill pet nation. And for his self-serving recommendation, Tim Schmeier will very shortly be on the job market. If you, your employeer, or someone you know is looking for data science talent, you can reach time at his gmail account which is timothy.schmeier at gmail dot com.
You can read Tim's write up titled Speed Cameras: Revenue or Public Safety? on the NYC Data Science Academy blog. His original write up, reproducible analysis, and figures are a great compliment to this episode.
For his benevolent recommendation, Tim suggests listeners visit Maddie's Fund - a data driven charity devoted to helping achieve and sustain a no-kill pet nation. And for his self-serving recommendation, Tim Schmeier will very shortly be on the job market. If you, your employeer, or someone you know is looking for data science talent, you can reach time at his gmail account which is timothy.schmeier at gmail dot com.
Released:
Feb 27, 2015
Format:
Podcast episode
Titles in the series (100)
[MINI] Bayesian Updating: 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. by Data Skeptic