In a test of significance (also called a hypothesis test), Type I error is the error of rejecting the null hypothesis when it is true — of saying an effect or event is statistically significant when it is not.
Yearly Archives: 2013
Predictive Modeling and Typhoon Relief
The devastation wrought by Super-Typhoon Haiyan in the Philippines is the biggest test yet for the nascent technology of “artificial intelligence disaster response,” a phrase used by Patrick Meier, a pioneer in the field. When disaster strikes, a flood of social media posts and tweets ensues. There is useful information in the data flood, butContinue reading “Predictive Modeling and Typhoon Relief”
Personality regions
There are Red States and Blue States. The three blue states of the Pacific coast constitute the Left Coast. For Colin Woodward, Yankeedom comprises both New England and the Great Lakes. If you’re into accessories, there’s the Bible Belt, the Rust Belt, and the Stroke Belt. In the Journal of Personality and Social Psychology (onlineContinue reading “Personality regions”
Week #49 – Data partitioning
Data partitioning in data mining is the division of the whole data available into two or three non-overlapping sets: the training set (used to fit the model), the validation set (used to compared models), and the test set (used to predict performance on new data).
Terrorist Clusters
The “righteous vengeance gun attack” is just one of 10 types of terrorism identified by Chenoweth and Lowham via statistical clustering techniques. Another cluster is “bombings of a public population where a liberation group takes responsibility.” You can read about the 10 clusters, and the 44 dichotomous variables (suicide or not, bombing or not, religiousContinue reading “Terrorist Clusters”
Statistics.com Partners With CrowdANALYTIX to Offer New Online Course With Crowdsource Contest As Project
Crowdsourcing, using the power of the crowd to solve problems, has been used for many functions and tasks, including predictive modeling (like the 2009 Netflix Contest). Typically, problems are broadcast to an unknown group of statistical modelers on the Internet, and solutions are sought. Every crowdsourced project harnesses the power of the community to findContinue reading “Statistics.com Partners With CrowdANALYTIX to Offer New Online Course With Crowdsource Contest As Project”
Week #43 – Longitudinal data
Longitudinal data records multiple observations over time for a set of individuals or units. A typical..
Week #42 – Cross-sectional data
Cross-sectional data refer to observations of many different individuals (subjects, objects) at a given time, each observation belonging to a different individual. A simple…
Week #32 – CHAID
CHAID stands for Chi-squared Automatic Interaction Detector. It is a method for building classification trees and regression trees from a training sample comprising already-classified objects.
Illuminate, Iterate, Involve, Involvement, Iteration, Insight
I did not start off in the field of statistics; my first real job was as a diplomat. And from my undergraduate days I recall a professor who taught a cultural history of Russia. He was one of the world’s top experts. Possessed of a tremendous store of knowledge (a leading author in the field,Continue reading “Illuminate, Iterate, Involve, Involvement, Iteration, Insight”
Week # 29 – Training data
Also called the training sample, training set, calibration sample. The context is predictive modeling (also called supervised data mining) – where you have data with multiple predictor variables and a single known outcome or target variable.
Mutual Attraction
Mutual attraction is a dominant force in the universe. Gravity binds the moon to the earth, the earth to the sun, the sun to the galaxy, and one galaxy to another. And yet the universe is expanding; the result is a larger universe comprised of elements that coalesce into clusters. Human history is much theContinue reading “Mutual Attraction”
Week #18 – Centroid
The centroid is a measure of center in multi-dimensional space.