Many introductions to Bayesian analysis use relatively simple didactic examples (e.g. making inference about the probability of success given bernoulli data). While this makes for a good introduction to Bayesian principles, the extension of these principles to regression is not straight-forward. This post will sketch out how these principles extend to simple linear regression. Along … Continue reading Bayesian Simple Linear Regression with Gibbs Sampling in R

# Tag: data science

# Exploring P-values with Simulations in R

The recent flare-up in discussions on p-values inspired me to conduct a brief simulation study. In particularly, I wanted to illustrate just how p-values vary with different effect and sample sizes. Here are the details of the simulation. I simulated $latex n $ draws of my independent variable $latex X $: $latex X_n \sim N(100, 400)$ where $latex … Continue reading Exploring P-values with Simulations in R

# Stop and Frisk: Spatial Analysis of Racial Differences

In my last post, I compiled and cleaned publicly available data on over 4.5 million stops over the past 11 years. I also presented preliminary summary statistics showing that blacks had been consistently stopped 3-6 times more than whites over the last decade in NYC. Since the last post, I managed to clean and reformat the … Continue reading Stop and Frisk: Spatial Analysis of Racial Differences

# Stop and Frisk: Blacks stopped 3-6 times more than Whites over 10 years

The NYPD provides publicly available data on stop and frisks with data dictionaries, located here. The data, ranging from 2003 to 2014, contains information on over 4.5 million stops. Several variables such as the age, sex, and race of the person stopped are included. I wrote some R code to clean and compile the data … Continue reading Stop and Frisk: Blacks stopped 3-6 times more than Whites over 10 years