Simulation - a Venerable History One of the most consequential and valuable analytical tools in business is simulation, which helps us make decisions in the face of uncertainty, such as these: An airline knows on average, what proportion of ticketed passengers show up for a…
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).
"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.)
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.
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 to…
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 (below), the Princeton statistician…
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,…
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…
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…
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…
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…
Two important statistical modeling courses are coming up in May. May 18 - Jun 15: Principal Components and Factor Analysis May 18 - Jun 15: Modeling Count Data Factor analysis is used frequently in social science research where you want to examine that which…
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.…
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…
"The customer is always right" was the motto Selfridge's department store coined in 1909. "We'll tell the customer what they want" was Madison Avenue's mantra starting in the 1950's. Now data scientists like Karolis Urbonas help companies like Amazon (where he works in Europe as…
Predicting whether an internet user will click on a link or buy a product, whether an insurance claim is fraudulent, whether a home mortgage will be paid on time (or early), how much a house will sell for, what internet ad you should see next,…
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…
"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…
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…
Today's Words of the Week are convolution and tensor, key components of deep learning.
Benford's law describes an expected distribution of the first digit in many naturally-occurring datasets.
Contingency tables are tables of counts of events or things, cross-tabulated by row and column.
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.
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.
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.
To some, NLP = natural language processing, a form of text analytics arising from the field of computational linguistics.
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:
Did you know that there is a country in which kidneys can be legally bought and sold? That country is Iran, and there are actually two models for payment. In one part of the country, donors receive a flat fee, and in the other part…
“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…
In statistics, "n" denotes the size of a dataset, typically a sample, in terms of the number of observations or records.
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…
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…
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…
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…
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,…
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…
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…
HDFS is the Hadoop Distributed File System. It is designed to accommodate parallel processing on clusters of commodity hardware, and to be fault tolerant.
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.
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).
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.
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.
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.…
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.
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.
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).
In discrete response models, overdispersion occurs when there is more correlation in the data than is allowed by the assumptions that the model makes.
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.
The predictors in a predictive model are sometimes given different terms by different disciplines. Traditional statisticians think in terms of variables.
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…
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…
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…
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).
There was an interesting article a couple of weeks ago in the New York Times magazine section on the role that Big Data can play in treating patients -- discovering things that clinical trials are too slow, too expensive, and too blunt to find. The…
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.
The classic illustration of the power of brand is perfume - expensive perfumes may cost just a few dollars to produce but can be sold for more than $500 due to the cachet afforded by the brand. David Malan's Computer Science course at Harvard, CSCI…
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…
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…
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.).
Goodness-of-fit measures the difference between an observed frequency distribution and a theoretical probability distribution which
An adjacency matrix describes the relationships in a network. Nodes are listed in the top..
Ever wonder why, in World War II, ships in convoys were safer than ships traveling on their own? Most people assume it was due to the protection afforded by military escort vessels, of which there was a limited supply (insufficient to protect ships traveling on…
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…
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…
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.
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…
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…
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).
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…
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…
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...
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.
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…
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 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…
The centroid is a measure of center in multi-dimensional space.
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,
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 ...
