“out-of-bag,” as in “out-of-bag error”

"Bag" refers to "bootstrap aggregating," repeatedly drawing of bootstrap samples from a dataset and aggregating the results of statistical models applied to the bootstrap samples. (A bootstrap sample is a resample drawn with replacement.)

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BOOTSTRAP

I used the term in my message about bagging and several people asked for a review of the bootstrap. Put simply, to bootstrap a dataset is to draw a resample from the data, randomly and with replacement.

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Same thing, different terms..

The field of data science is rife with terminology anomalies, arising from the fact that the field comes from multiple disciplines.

 

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100 years of variance

It is 100 years since R A Fischer introduced the concept of "variance" (in his 1918 paper "The Correlation Between Relatives on the Supposition of Mendelian Inheritance"). There is much that statistics has given us in the century that followed. Randomized clinical trials, and the means…

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Early Data Scientists

Casting back long before the advent of Deep Learning for the "founding fathers" of data science, at first glance you would rule out antecedents who long predate the computer and data revolutions of the last quarter century. But some consider John Tukey (right), the Princeton statistician…

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Python for Analytics

Python started out as a general purpose language when it was created in 1991 by Guido van Rossum. It was embraced early on by Google founders Sergei Brin and Larry Page ("Python where we can, C++ where we must" was reputedly their mantra). In 2006,…

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Course Spotlight: Deep Learning

Deep learning is essentially "neural networks on steroids" and it lies at the core of the most intriguing and powerful applications of artificial intelligence. Facial recognition (which you encounter daily in Facebook and other social media) harnesses many levels of data science tools, including algorithms…

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Course Spotlight: Structural Equation Modelling (SEM)

SEM stands for "structural equation modeling," and we are fortunate to have Prof. Randall Schumacker teaching this subject at Statistics.com. Randy created the Structural Equation Modeling (SEM) journal in 1994 and the Structural Equation Modeling Special Interest Group (SIG) at the American Educational Research Association…

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Benford’s Law Applies to Online Social Networks

Fake social media accounts and Russian meddling in US elections have been in the news lately, with Mark Zuckerberg (Facebook founder) testifying this week before the US Congress. Dr. Jen Golbeck, who teaches Network Analysis at Statistics.com, published an ingenious way to determine whether a…

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The Real Facebook Controversy

Cambridge Analytica's wholesale scraping of Facebook user data is big news now, and people are shocked that personal data is being shared and traded on a massive scale on the internet. But the real issue with social media is not harming to individual users whose…

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Masters Programs versus an Online Certificate in Data Science from Statistics.com

We just attended the analytics conference of INFORMS' (The Institute for Operations Research and the Management Sciences) this week in Baltimore, and they held a special meeting for directors of academic analytics programs to better align what universities are producing with what industry is seeking.…

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Course Spotlight: Likert scale assessment surveys

Do you work with multiple choice tests, or Likert scale assessment surveys? Rasch methods help you construct linear measures from these forms of scored observations and analyze the results from such surveys and tests. "Practical Rasch Measurement - Core Topics" In this course, you will…

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Course Spotlight: Spatial Statistics Using R

Have you ever needed to analyze data with a spatial component? Geographic clusters of disease, crimes, animals, plants, events?Or describing the spatial variation of something, and perhaps correlating it with some other predictor? Assessing whether the geographic distribution of something departs from randomness? Location data…

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“Money and Brains” and “Furs and Station Wagons”

"Money and Brains" and "Furs and Station Wagons" were evocative customer shorthands that the marketing company Claritas came up with over a half century ago. These names, which facilitated the work of marketers and sales people, were shorthand descriptions of segments of customers identified through…

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Course Spotlight: Text Mining

The term text mining is sometimes used in two different meanings in computational statistics: Using predictive modeling to label many documents (e.g. legal docs might be "relevant" or "not relevant") - this is what we call text mining. Using grammar and syntax to parse the…

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BENFORD’S LAW

Benford's law describes an expected distribution of the first digit in many naturally-occurring datasets.

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HYPERPARAMETER

Hyperparameter is used in machine learning, where it refers, loosely speaking, to user-set parameters, and in Bayesian statistics, to refer to parameters of the prior distribution.

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SAMPLE

Why sample? A while ago, sample would not have been a candidate for Word of the Week, its meaning being pretty obvious to anyone with a passing acquaintance with statistics. I select it today because of some output I saw from a decision tree in Python.

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SPLINE

 

The easiest way to think of a spline is to first think of linear regression - a single linear relationship between an outcome variable and various predictor variables. 

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NLP

To some, NLP = natural language processing, a form of text analytics arising from the field of computational linguistics.

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OVERFIT

As applied to statistical models - "overfit" means the model is too accurate, and fitting noise, not signal. For example, the complex polynomial curve in the figure fits the data with no error, but you would not want to rely on it to predict accurately for new data:

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Quotes about Data Science

“The goal is to turn data into information, and information into insight.” – Carly Fiorina, former CEO, Hewlett-Packard Co. Speech given at Oracle OpenWorld “Data is the new science. Big data holds the answers.” – Pat Gelsinger, CEO, EMC, Big Bets on Big Data, Forbes“Hiding within those…

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Week #18 – n

In statistics, "n" denotes the size of a dataset, typically a sample, in terms of the number of observations or records.

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Week #17 – Corpus

A corpus is a body of documents to be used in a text mining task.  Some corpuses are standard public collections of documents that are commonly used to benchmark and tune new text mining algorithms.  More typically, the corpus is a body of documents for…

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Historical Spotlight: Eugenics – journey to the dark side at the dawn of statistics

April 27 marks the 80th anniversary of the death of Karl Pearson, who contributed to statistics the correlation coefficient, principal components, the (increasingly-maligned) p-value, and much more. Pearson was one of a trio of founding fathers of modern statistics, the others being Francis Galton and…

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Week #2 – Casual Modeling

Causal modeling is aimed at advancing reasonable hypotheses about underlying causal relationships between the dependent and independent variables. Consider for example a simple linear model: y = a0 + a1 x1 + a2 x2 + e where y is the dependent variable, x1 and x2…

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Week #10 – Arm

In an experiment, an arm is a treatment protocol - for example, drug A, or placebo.   In medical trials, an arm corresponds to a patient group receiving a specified therapy.  The term is also relevant for bandit algorithms for web testing, where an arm consists…

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Week #9 – Sparse Matrix

A sparse matrix typically refers to a very large matrix of variables (features) and records (cases) in which most cells are empty or 0-valued.  An example might be a binary matrix used to power web searches - columns representing search terms and rows representing searches,…

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Week #8 – Homonyms department: Sample

We continue our effort to shed light on potentially confusing usage of terms in the different data science communities. In statistics, a sample is a collection of observations or records.  It is often, but not always, randomly drawn.  In matrix form, the rows are records…

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Week #7 – Homonyms department: Normalization

With this entry, we inaugurate a new effort to shed light on potentially confusing usage of terms in the different data science communities. In statistics and machine learning, normalization of variables means to subtract the mean and divide by the standard deviation.  When there are…

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Week #43 – HDFS

HDFS is the Hadoop Distributed File System.  It is designed to accommodate parallel processing on clusters of commodity hardware, and to be fault tolerant.

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Week #42 – Kruskal – Wallis Test

The Kruskal-Wallis test is a nonparametric test for finding if three or more independent samples come from populations having the same distribution. It is a nonparametric version of ANOVA.

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Week #32 – False Discovery Rate

A "discovery" is a hypothesis test that yields a statistically significant result. The false discovery rate is the proportion of discoveries that are, in reality, not significant (a Type-I error). The true false discovery rate is not known, since the true state of nature is not known (if it were, there would be no need for statistical inference).

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Week #23 – Netflix Contest

The 2006 Netflix Contest has come to convey the idea of crowdsourced predictive modeling, in which a dataset and a prediction challenge are made publicly available.  Individuals and teams then compete to develop the best performing model.

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Week #20 – R

This week's word is actually a letter.  R is a statistical computing and programming language and program, a derivative of the commercial S-PLUS program, which, in turn, was an offshoot of S from Bell Labs.

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Be Smarter Than Your Devices: Learn About Big Data

When Apple CEO Tim Cook finally unveiled his company's new Apple Watch in a widely-publicized rollout earlier this month, most of the press coverage centered on its cost ($349 to start) and whether it would be as popular among consumers as the iPod or iMac.…

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Week #16 – Moving Average

In time series forecasting, a moving average is a smoothing method in which the forecast for time t is the average value for the w periods ending with time t-1.

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Week #15 – Interaction term

In regression models, an interaction term captures the joint effect of two variables that is not captured in the modeling of the two terms individually.

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Week #14 – Naive forecast

A naive forecast or prediction is one that is extremely simple and does not rely on a statistical model (or can be expressed as a very basic form of a model).

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week #9 – Overdispersion

In discrete response models, overdispersion occurs when there is more correlation in the data than is allowed by the assumptions that the model makes.

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Week #8 – Confusion matrix

In a classification model, the confusion matrix shows the counts of correct and erroneous classifications.  In a binary classification problem, the matrix consists of 4 cells.

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Week #5 – Features vs. Variables

The predictors in a predictive model are sometimes given different terms by different disciplines.  Traditional statisticians think in terms of variables.

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Course Spotlight: The Text Analytics Sequence

Text analytics or text mining is the natural extension of predictive analytics, and Statistics.com's text analytics program starts Feb. 6. Text analytics is now ubiquitous and yields insight in: Marketing: Voice of the customer, social media analysis, churn analysis, market research, survey analysis Business: Competitive…

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Course Spotlight: Constrained Optimization

Say you operate a tank farm (to store and sell fuel). How much of each fuel grade should you buy? You have specified flow and storage capacities, constraints on what types of fuels can be stored in which tanks, prior contractual obligations about minimum monthly…

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Week # 52 – Quasi-experiment

In social science research, particularly in the qualitative literature on program evaluation, the term "quasi-experiment" refers to studies that do not involve the application of treatments via random assignment of subjects.

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College Credit Recommendation

Statistics.com Receives College Recommendation from the American Council on Education (ACE) College Credit Recommendation for Online Data Science Courses from The Institute for Statistics Education at Statistics.com LLC The American Council on Education's College Credit Recommendation Service (ACE CREDIT) has evaluated and recommended college credit…

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Week #48 – Structured vs. unstructured data

Structured data is data that is in a form that can be used to develop statistical or machine learning models (typically a matrix where rows are records and columns are variables or features).

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Word #39 – Censoring

Censoring in time-series data occurs when some event causes subjects to cease producing data for reasons beyond the control of the investigator, or for reasons external to the issue being studied.

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Twitter Sentiment vs. Survey Methods

Nobody expects Twitter feed sentiment analysis to give you unbiased results the way a well-designed survey will. A Pew Research study found that Twitter political opinion was, at times, much more liberal than that revealed by public opinion polls, while it was more conservative at…

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Internet of Things

Boston, August 3 2014: Bill Ruh, GE Software Center, says that the Internet of Things, 30 billion machines talking to one another, will dwarf the impact of the consumer internet. Speaking at the Joint Statistical Meetings today, Ruh predicted that the marriage of the IoT…

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Work #32 – Predictive modeling

Predictive modeling is the process of using a statistical or machine learning model to predict the value of a target variable (e.g. default or no-default) on the basis of a series of predictor variables (e.g. income, house value, outstanding debt, etc.).

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Week #29 – Goodness-of-fit

Goodness-of-fit measures the difference between an observed frequency distribution and a theoretical probability distribution which

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Dialects

When talking to several people, do you address them as "you guys"? "Y'all"? Just "you"? And is the carbonated soft drink "soda" or "pop?" Maps based on survey responses to questions like this were published in the Harvard Dialect Survey in 2003. Josh Katz took…

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Needle in a Haystack

What's the probability that the NSA examined the metadata for your phone number in 2013? According to John Inglis, Deputy Director at the NSA, it's about 0.00001, or 1 in 100,000. A surprisingly small number, given what we've all been reading in the media about…

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Week #53 – Effect size

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.

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Week #51 – Type 1 error

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.

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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…

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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).

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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…

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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…

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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...

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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.

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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.

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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…

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Churn Trigger

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.

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Congratulations to Thomas Lumley!

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

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Julian Simon birthday

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

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Statistics for Future Presidents

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!

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The Data Scientist

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.

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Coffee causes cancer?

"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).

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The sacrifice bunt

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

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Epidemiologist joke

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.

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The Power of Round

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

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