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In predictive modeling, ensemble methods refer to the practice of taking multiple models and averaging their predictions.

The expected value of a random variable, in a simple sense, is nothing but the arithmetic mean.

Exact tests are hypothesis tests that are guaranteed to produce Type-I error at or below the nominal alpha level of the test when conducted on samples drawn from a null model.

In statistical models, error or residual is the deviation of the estimated quantity from its true value: the greater the deviation, the greater the error.

Endogenous variables in causal modeling are the variables with causal links (arrows) leading to them from other variables in the model.

In a study or experiment with two groups (usually control and treatment), the investigator typically has in mind the magnitude of the difference between the two groups that he or she wants to be able to detect in a hypothesis test.

In the interim monitoring of clinical trials, multiple looks are taken at the accruing patient results - say, response to a medication.

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.

A time series x(t); t=1,... is considered to be stationary if its statistical properties do not depend on time t .

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).

Data mining is concerned with finding latent patterns in large databases.

An observation´s z-score tells you the number of standard deviations it lies away from the population mean (and in which direction).

In multivariate analysis, cluster analysis refers to methods used to divide up objects into similar groups, or, more precisely, groups whose members are all close to one another on various dimensions being measured.

In psychology, a construct is a phenomenon or a variable in a model that is not directly observable or measurable  - intelligence is a classic example.

Collaborative filtering algorithms are used to predict whether a given individual might like, or purchase, an item.

Longitudinal data records multiple observations over time for a set of individuals or units. A typical..

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...

Tokenization is an initial step in natural language processing.  It involves breaking down a text into a series of basic units, typically words. For example...

A natural language is what most people outside the field of computer science think of as just a language (Spanish, English, etc.). The term...

White Hat Bias is bias leading to distortion in, or selective presentation of, data that is considered by investigators or reviewers to be acceptable because it is in the service of righteous goals.

An edge is a link between two people or entities in a network that can be

Stratified sampling is a method of random sampling.

When probabilities are quoted without specification of the sample space, it could result in ambiguity when the sample space is not self-evident.

A discrete distribution is one in which the data can only take on certain values, for example integers.  A continuous distribution is one in which data can take on any value within a specified range (which may be infinite).

The central limit theorem states that the sampling distribution of the mean approaches Normality as the sample size increases, regardless of the probability distribution of the population from which the sample is drawn.

Classification and regression trees (CART) are a set of techniques for classification and prediction.

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.

In a census survey , all units from the population of interest are analyzed. A related concept is the sample survey, in which only a subset of the population is taken.

Discriminant analysis is a method of distinguishing between classes of objects.  The objects are typically represented as rows in a matrix.

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.

A general statistical term meaning a systematic (not random) deviation of an estimate from the true value.

One of several computer-based iterative procedures for selecting variables to use in a model.  The process begins...

Outcomes to an experiment or repeated events are statistically significant if they differ from what chance variation might produce.

In multiple comparison procedures, family-wise type I error is the probability that, even if all samples come from the same population, you will wrongly conclude

A cohort study is a longitudinal study that identifies a group of subjects sharing some attributes (a "cohort") then

The coefficient of variation is the standard deviation of a data set, divided by the mean of the same data set.

In regression analysis, the coefficient of determination is a measure of goodness-of-fit (i.e. how well or tightly the data fit the estimated model).  The coefficient is

An estimator is a measure or metric intended to be calculated from a sample drawn from a larger population...

In regression analysis , collinearity of two variables means that strong correlation exists between them, making it difficult or impossible to estimate their individual regression coefficients reliably.

A cohort study is a longitudinal study that identifies a population or large group (a "cohort") then draws a sample from the population at various points in time and records data for the sample.

The centroid is a measure of center in multi-dimensional space.

Bootstrapping is sampling with replacement from observed data to estimate the variability in a statistic of interest. See also permutation tests, a related form of resampling. A common application

A Binomial distribution is used to describe an experiment, event, or process for which the probability of success is the same for each trial and each trial has only two possible outcomes.

A combination of treatment comparisons (e.g. send a sales solicitation, or send nothing) and predictive modeling to determine which cases or subjects respond (e.g. purchase or not) to which treatments.

Network analytics is the science of describing and, especially, visualizing the connections among objects.

Multiplicity issues arise in a number of contexts, but they generally boil down to the same thing:  repeated looks at a data set in different ways, until something "statistically significant" emerges.

Support vector machines are used in data mining (predictive modeling, to be specific) for classification of records, by learning from training data.

In data analysis or data mining, an attribute is a characteristic or feature that is measured for each observation (record) and can vary from one observation to another.  It might

The negative binomial distribution is the probability distribution of the number of Bernoulli (yes/no) trials required to obtain r successes.

A random walk is a process of random steps, motions, or transitions.  It might be in one dimension (movement along a line), in two dimensions (movements in a plane), or in three dimensions or more.

Cover time is the expected number of steps in a random walk required

is a general computer-intensive approach used in estimating the accuracy of statistical models.

(also called dissimilarity matrix) describes pairwise distinction between M objects.

in discrete time is the transformation of the series to a new time series where the values are the differences between consecutive values of the original series.

(outcome or variable) means "having only two possible values", e.g.

A probability density function is a curve used

In predictive modeling, data partitioning is the division of the data available for analysis into two or three non-overlapping

Promoting better understanding of statistics throughout the world.

New Editor of Journal of Statistics Education

Read Peter's Letter to the Editor in Saturday's Washington Post.

Last year's popular story out of the Predictive Analytics World conference series was Andrew Pole's presentation of Target's methodology for predicting which customers were pregnant.

Evidence show that there is no significant difference between taking an online introductory statistics course and a traditional in-person class.

Facebook began trading around 11:30 this morning, and I spent 8 minutes

Newly elected American Statistical Association (ASA) Fellow, and recognized for his outstanding professional contributions to and leadership in the field of statistical science.

Arizona's immigration law goes before the Supreme Court this week...

I saw this job posting a while ago, and, in my next life,

David Unwin, Emeritus Chair in Geography, Bubeck College, University of London (and instructor at Statistics.com!) will be awarded the Association of American Geographers (AAG) Ronald F. Abler Distinguished Service Honors at the upcoming annual meeting next week.

February 12 was the 80th anniversary of the birth of Julian Simon, an early pioneer in resampling methods.

Statistics for Future Presidents - Steve Pierson, Director of Science Policy at ASA wrote interesting blog wondering how statistics for future presidents (or policymakers more generally) would compare with the recommended statistical skills/concepts for others. Take a look and let him know!

Teaching Geographic Information Science and Technology in Higher Education, 2012 (Wiley)

The story of the prospective Facebook IPO, and prior IPO's from LinkedIn, Pandora, and Groupon all involve "data scientists".  Read an interview with Monica Rogati - Senior Data Scientist at LinkedIn to see the connection.

Dr. Michelle Everson is recognized for her outstanding contributions to and innovation in the teaching of elementary statistics.

John Elder's presentations on common data mining mistakes are a must-see if you have any experience or plans in the data mining arena.

"Any claim coming from an observational study is most likely to be wrong." Thus begins "Deming, data and observational studies," just published in "Significance Magazine" (Sept. 2011).

I was watching a Washington Nationals game on TV a couple of days ago, and the concept of "expected value" ...

A neurosurgeon, pathologist and epidemiologist are each told to examine a can of sardines on a table in a closed room, and present a report.

What do teenagers want? More importantly for the music industry, what music will they buy?

Advertisers shy away from round numbers, believing that $99 appears significantly cheaper than $100...

Did the NCAA get the March Madness rankings right? Check out SportsMeasures.com

What does Matt Asher's article "Attack of the Hair Trigger Bees" have to do with global warming? Matt Asher runs statisticsblog.com ...

The first Gallup Poll was published in October, 1935. In America Speaks,

Thinking about careers that use statistics? The job title "catastrophe modeling assistant" caught my eye recently in a job announcement. ...