P-Values – Are They Needed?

Five years ago last month, the psychology journal Basic and Applied Social Psychology instigated a major debate in statistical circles when it said it would remove p-value citations from papers it published.  A year later, the American Statistical Association (ASA) released a statement on p-values…

Comments Off on P-Values – Are They Needed?

Covid-19 Parameters

There are many moving parts in modeling the spread of an epidemic, a subject that has lately attracted the attention of great numbers of statistically-oriented non-epidemiologists (like me).  I’ve put together a “lay statistician’s guide” to some of the important parameters and factors (and I…

Comments Off on Covid-19 Parameters

Coronavirus – in Search of the Elusive Denominator

Anyone with internet access these days has their eyes on two constellations of data - the spread of the coronavirus, and the resulting collapse of the financial markets.  Following the 13% one-day drop of the stock market a week ago, The Wall Street Journal forecast…

Comments Off on Coronavirus – in Search of the Elusive Denominator

Ensemble Learning

In his book, The Wisdom of Crowds, James Surowiecki recounts how Francis Galton, a prominent statistician from the 19th century, attended an event at a country fair in England where the object was to guess the weight of an ox.   Individual contestants were relatively well…

Comments Off on Ensemble Learning

Big Sample, Unreliable Result

Which would you rather have?  A large sample that is biased, or a representative sample that is small?  The American Statistical Association committee that reviewed the 1948 Kinsey report on male sexual behavior, based on interviews with over 5000 men, left no doubt of their…

Comments Off on Big Sample, Unreliable Result

Mixed Models – When to Use

Companies now have a lot of data on their customers at an individual level.  Suppose you are tasked with forecasting customer spending at a grocery chain, and you want to understand how customer attributes, local economic factors, and store issues affect customer spending. You could…

Comments Off on Mixed Models – When to Use

The Normal Share of Paupers

In 2009, China began regional pilot programs that repurposed credit scores to a broader purpose - scoring a person’s “social credit.”  100 years earlier, at the height of the eugenics craze, the famous statistician Francis Galton undertook to repurpose statistical concepts in service of social…

Comments Off on The Normal Share of Paupers

UpLift and Persuasion

The goal of any direct mail campaign, or other messaging effort, is to persuade somebody to do something.  In the business world, it is usually to buy something. In the political world, it is usually to vote for someone (or, if you think you know…

Comments Off on UpLift and Persuasion

Lift and Persuasion

Predicting the probability that something or someone will belong to a certain category (classification problems) is perhaps the oldest type of problem in analytics.  Consider the category “repays loan.” Equifax, the oldest of the agencies that provides credit scores, was founded in 1899 as the…

Comments Off on Lift and Persuasion

Going Beyond the Canary Trap

In 2008, Elon Musk was concerned about leaks of sensitive information at Tesla Motors.  To catch the leaker, he prepared multiple unique versions of a new nondisclosure agreement he asked senior officers to sign.  Whichever version got leaked would reveal the leak source. This is…

Comments Off on Going Beyond the Canary Trap

Statistics.com Acquired by Elder Research

In last week’s Brief I described how The Institute’s courses, and its Mastery, Certificate and Degree programs would continue without interruption, following our acquisition by Elder Research, Inc.  Now I’d like to talk about how the Institute’s students stand to gain from the expertise and…

Comments Off on Statistics.com Acquired by Elder Research

PRESS RELEASE: STATISTICS.COM ACQUIRED BY ELDER RESEARCH

Statistics.com Acquired by Elder Research Acquisition Will Provide Focused Corporate and Individual Analytics Training Arlington, VA, January 29, 2020 - The Institute for Statistics Education at Statistics.com is excited to announce that it has been acquired by Elder Research, Inc, a Machine Learning, Data Science,…

Comments Off on PRESS RELEASE: STATISTICS.COM ACQUIRED BY ELDER RESEARCH

Choosing the Right Analytics Problem

The “streetlight effect:”  A man is looking for his keys under a streetlight.   Policeman:  “Where did you lose them?”   Man:  “In the alley, near the door to the bar.”   Policeman:  “Why are you looking here?”   Man:  “The light’s better.”   This is related to the more…

Comments Off on Choosing the Right Analytics Problem

Ethical Dilemmas in Data Science

Know those ads that follow you around the web, as a result of tracking cookies?  Many see them as an invasion of privacy, and EU rules made them subject to user consent.  Google recently announced that Chrome will eventually stop supporting these cookies.  A win…

Comments Off on Ethical Dilemmas in Data Science

Not Glamorous, But Lucrative

What do stormy days, weekend evenings, and the last day of the month have in common?  They are all good times to negotiate a good price for a new car. Inclement days yield less customer traffic in auto showrooms, which is good for the buyer. …

Comments Off on Not Glamorous, But Lucrative

Simulating the Complex Sale

Every 30 minutes a new business book is published; many of them purport to teach effective selling.  Most of them make sense, but solid quantitative analysis is rarely on the front burner. This is strange, because effective selling requires demonstrating value.  Sales professionals are taught…

Comments Off on Simulating the Complex Sale

Analytics Meets the Cardboard Box

“Do you have a bag?“ or “Would you like a bag?” have become common parts of the brick-and-mortar retail transaction.  Reusable bags, or simply doing without, have reduced the flow of plastic and paper into recycling.   E-commerce is a different matter.  I just unpacked a…

Comments Off on Analytics Meets the Cardboard Box

Detecting a Slots Payout Difference of 2%

Most businesses use statistics and analytics to one degree or another, but there is only one industry that is built solely on this discipline.  This week we look at the casino business - in particular, the odds on slots. Slot machines are a casino’s best…

Comments Off on Detecting a Slots Payout Difference of 2%

Betting and Statistics

Betting has had a long and close relationship with the science of probability and statistics.  In the mid-1600’s, the French intellectual and gambler Antoine Gombaud, who called himself Chevalier de Méré, enlisted the help of the mathematician Blaise Pascal to solve several puzzles involving dice…

Comments Off on Betting and Statistics

Unforeseen Consequences in Data Science

Unforeseen Consequences in Data Science After the massive Exxon Valdez oil spill, states passed laws boosting the liability of tanker companies for future spills.  The result was not as intended: fly-by-night companies, whose bankruptcy would not be consequential, took over the trade. In this blog…

Comments Off on Unforeseen Consequences in Data Science

Data Analytics

Terminology in Data Analytics As data continue to grow at a faster rate than either population or economic activity, so do organizations' efforts to deal with the data deluge, and use it to capture value.  And so do the methods used to analyze data, which…

Comments Off on Data Analytics

Data Analytics Courses

Data analytics and data science are popular terms, and skills in these areas are in great demand.  But what do these terms mean?  Below is an overview and a listing of related courses. For information about our certificate programs in data science and analytics, click here.…

Comments Off on Data Analytics Courses

Statistical Thinking

Gambler’s Fallacy I - forgetting that the “coin has no memory”   Gamblers often believe that after a long streak of one outcome, the probability of a different outcome has increased.  Sports commentators often say that a batter in a slump is “due” for a hit.…

Comments Off on Statistical Thinking

Machine Learning and Human Bias

Does better AI offer the hope of prejudice-free decision-making?  Ironically, the reverse might be true, especially with the advent of deep learning.   Bias in hiring is one area where private companies move with great care, since there are thickets of laws and regulations in most…

Comments Off on Machine Learning and Human Bias

Anomaly Detection via Conversation: “How was your vacation?”

A friendly query about your holiday might be a question you get from a roaming agent in the check-in area at the Tel Aviv airport.  Israel, considered to have the most effective airport security in the world, does not rely solely on routine mechanical screening…

Comments Off on Anomaly Detection via Conversation: “How was your vacation?”

Meta Analysis

1.2 million scientific papers were indexed by PubMed in 2011 (see Are Scientists Doing Too Much Research), ample proof that there are lots of people studying the same or similar things.  For example, there have been Over 100 studies of suicide following psychiatric institutionalization     38 studies…

Comments Off on Meta Analysis

Explain or Predict?

A casual user of machine learning methods like CART or naive Bayes is accustomed to evaluating a model by measuring how well it predicts new data.  When examining the output of statistical models, they are often flummoxed by the profusion of assessment metrics. Typical multiple…

Comments Off on Explain or Predict?

Social Network Analysis (SNA) in Medicine

In hospitals, “sentinel events” are events that carry with them a significant risk of unexpected death or harm.  It is estimated that ⅔ of such sentinel events result from communications failures during the handoff of a patient from one provider to another (e.g. during a…

Comments Off on Social Network Analysis (SNA) in Medicine

Matching Algorithms

Some applications of machine learning and artificial intelligence are recognizably impressive - predicting future hospital readmission of discharged patients, for example, or diagnosing retinopathy. Others - self-driving cars, for example - seem almost magical. The matching problem, though, is one where your first reaction might…

Comments Off on Matching Algorithms

Confusing Terms in Data Science – A Look at Synonyms, Homonyms and more

To a statistician, a sample is a collection of observations (cases). To a machine learner, it's a single observation. Modern data science has its origin in several different fields, which leads to potentially confusing homonyms and synonyms, like these: Homonyms (words with multiple meanings): Bias: To…

Comments Off on Confusing Terms in Data Science – A Look at Synonyms, Homonyms and more

Handling the Noise – Boost It or Ignore It?

In most statistical modeling or machine learning prediction tasks, there will be cases that can be easily predicted based on their predictor values (signal), as well as cases where predictions are unclear (noise). Two statistical learning methods, boosting and ProfWeight, use those difficult cases in…

Comments Off on Handling the Noise – Boost It or Ignore It?

Good to Great

In 1994, Jim Collins and Jerry Porras, former and current Stanford professors, published the best-seller Built to Last that described how "long-term sustained performance can be engineered into the DNA of an enterprise."  It sold over a million copies. Buoyed by that success, Collins and a…

Comments Off on Good to Great

Work and Heat

If you are working on New Year's Eve or New Year's Day, odds are it is from home, where you can (usually) control the temperature in the home. Which, from the standpoint of productivity, is a good thing. According to a study from Cornell, raising…

Comments Off on Work and Heat

The False Alarm Conundrum

False alarms are one of the most poorly understood problems in applied statistics and biostatistics. The fundamental problem is the wide application of a statistical or diagnostic test in search of something that is relatively rare. Consider the Apple Watch's new feature that detects atrial…

Comments Off on The False Alarm Conundrum

GE Regresses to the Mean

Thirty years ago, GE became the brightest star in the firmament of statistical ideas in business when it adopted Six Sigma methods of quality improvement. Those methods had been introduced by Motorola, but Jack Welch's embrace of the same methods at GE, a diverse manufacturing…

Comments Off on GE Regresses to the Mean

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…

Comments Off on Benford’s Law Applies to Online Social Networks

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…

Comments Off on The Real Facebook Controversy

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.…

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

“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…

Comments Off on “Money and Brains” and “Furs and Station Wagons”

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…

Comments Off on Quotes about Data Science

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…

Comments Off on College Credit Recommendation

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…

Comments Off on Needle in a Haystack

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…

Comments Off on Personality regions

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…

Comments Off on Mutual Attraction
Close Menu