# 2130 search results for "regression"

## What Can Go Wrong: My Favorite Example

April 28, 2014
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I’m one of many who bemoan the fact that statistics is typically thought of as — alas, even taught as — a set of formula plugging methods. One enters one’s data, turns the key, and the proper answers pop out. This of course is not the case at all, and arguably statistics is as much

## Introducing Statwing

April 27, 2014
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Recently, Greg Laughlin, the founder of a new statistical software called Statwing, let me try his product for free. I happen to like free things very much (the college student is strong within me) so I gave it a try. I mostly like how easy it is to use: For instance, to relate two attributes

## There is no “Too Big” Data, is there?

April 23, 2014
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$Y_i\sim\mathcal{B}(p_i)$

A few years ago, a former classmate came back to me with a simple problem. He was working for some insurance company (and still is, don’t worry, chatting with me is not yet a reason for dismissal), and his problem was that their dataset was too large to run (standard) codes to get a regression, and some predictions. My...

## Yet Another Baseball Defense Statistic

April 22, 2014
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Fangraphs recently published an interesting dataset that measures defensive efficiency of fielders. For each player, the Inside Edge dataset breaks their opportunities to make plays into five categories, ranging from almost impossible to routine. It al...

April 21, 2014
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The latest issue of the American Statistician has a set of thought-provoking point/counterpoint papers on Simpson’s Paradox, with a tie-in to the controversial issue of causality. (I will not address the causality issue here.) Since I have long had my own thoughts about Simpson’s, I’ll postpone the topic I had planned to post this week,

April 21, 2014
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The latest issue of the American Statistician has a set of thought-provoking point/counterpoint papers on Simpson’s Paradox, with a tie-in to the controversial issue of causality. (I will not address the causality issue here.) Since I have long had my own thoughts about Simpson’s, I’ll postpone the topic I had planned to post this week,

## Mythbusting – Dr. Copper

April 21, 2014
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Image by Justin Reznick   “An economist is an expert who will know tomorrow why the things he predicted yesterday didn't happen today.” Laurence J. Peter (author and creator of the Peter Principle) If you were paying attention to financial sites last month, you probably noticed a number of articles on “Dr. Copper”. Here is

## Fracking and House Prices on the Marcellus Shale

April 21, 2014
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Starting last summer I worked on a short project that set out to estimate the potential costs of externalities due to unconventional shale gas production in the Marcellus shale on local house prices using a dataset of roughly 150,000 recently sold houses in Ohio, West Virginia and Pennsylvania. I stopped working on a project that

## Webinar: Big-Data Trees for R

April 21, 2014
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If you missed last week's webinar presented by Revolution Analytics' US Chief Scientist Mario Inchiosa, Decision Trees built in Hadoop plus more Big Data Analytics with Revolution R Enterprise, the slides and webinar replay are now available for download. The webinar includes a demo of building decision trees and regression trees in Revolution R Enterprise, and using the Tree...

## Using Markov Chains to Model Mortgage Defaults in R

April 18, 2014
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The goal of this post is to blend the material I’ve been learning in my night class with my day-job and R. If we have some object that switches between states over time according to fixed probabilities, we can model the long-term behavior of this object using Markov chains*. A good example is a mortgage. … Continue reading...