“In the age of Big Data we often believe that our predictions about the future are better than ever before. But ...in the real world, we often get better results by using simple rules and considering less information.” (From a review of Gerd Gigerenzer’s Data Savvy)…
A famous business school case by Harvard Professor Michael Porter on forecasting chainsaw sales dramatically illustrated the limits of statistical models when common business sense and clear-eyed thinking are missing. In the chainsaw case, students were asked to forecast the future U.S. demand for chainsaws,…
In deployed machine learning pipelines, “drift” is changes in the model environment that cause the model performance to degrade over time. Drift might result from data quality changes. For example, increasing amounts of missing values in the input data. Or a company might alter the…
This week we look at several case studies where success on the AI front was not sufficient to assure longer term business success. Our course spotlight is on: Aug 20 - Sep 17: Introduction to Design of Experiments Learn how to design experiments (especially costly…
Who would have thought that an entire book devoted to the bias-variance tradeoff would make it to the NY Times business best seller list? The book is the recently-published Noise, by Daniel Kahneman, Olivier Sibony and Cass R. Sunstein, and, as of the beginning of…
A common problem in machine learning is the “rare case” situation. In many classification problems, the class of interest (fraud, purchase by a web visitor, death of a patient) is rare enough that a data sample may not have enough instances to generate useful predictions.…
In their book Mining your Own Business, Jeff Deal and Gerhard Pilcher, COO and CEO of Elder Research respectively, describe what I'll call “The Case of the Climbing Churn.” Churn is when a subscriber cancels or fails to renew a service or subscription. A successful…
This week we look at odds and betting; our course spotlights are July 23 -Aug 20: SQL - Responsible Data ScienceJuly 30 -Aug 27: SQL - Biostatistics 1 - For Medical Science and Public Health See you in class! - Peter BruceFounder of The Institute for Statistics…
Epidemiological terms are top of mind now, due to the pandemic. Here are two that often confuse: incidence and prevalence. For example, I encountered the following sentence on a popular medical web site: “Knee meniscal injuries are common with an incidence of 61 cases per…
In your introductory statistics class, probability took center stage. Odds were for gamblers. But it turns out odds play an important role in statistics, too. The relationship between the two is simple. To estimate the probability that event “A” will happen, we divide the number…
This week we look at the increasingly important role of data engineers. Our spotlight is on our Programming for Data Science certificate program -you can start in July with July 9 -Aug 6: SQL - Introduction to Database Queries See you in class! - Peter…
An often-overlooked basic part of learning new things is vocabulary: if you don’t fully understand the meaning of terms, you are handicapped. Worse, if you think you do understand, but that understanding is wrong, you are deprived of the ability to identify the gap in…
This week we discuss data leaks, which can render apparently well-performing machine learning models useless. Our spotlight is on the Thomas Edison University Data Science Analytics Master’s Program, which was developed in partnership with Statistics.com See you in class! - Peter BruceFounder of The Institute…
He spoke with Val Woodside, our Customer Success Specialist at Statistics.com about his experience in the certificate program. Tell us about your experience at Statistics.com? It was excellent. For me it was the first time that I studied through this online process. You have to…
Good psychics have a knack for getting their audience to reveal, unwittingly, information that can be turned around and used in a prediction. Statisticians and data scientists fall prey to a related phenomenon, leakage, when they allow into their models highly predictive features that would…
This week we spotlight our introductory statistics courses, and take a look at supposed “need to know” statistical concepts for data science. See you in class! - Peter BruceFounder of The Institute for Statistics Education at Statistics.com ................................... News You Need to Know What’s happening…
This week we look at a backdoor method to make predictions come true. Our student spotlight is on Staci Taylor, Assistant Prof. of Nursing at Southeastern Louisiana State Univ., and our featured programs are: Analytics for Data Science Biostatistics See you in class! -…
The classic Gambler’s Ruin puzzle has an actuarial parallel: “Ruin Theory,” the calculations that govern what an insurance company should charge in premiums to reduce the probability of “ruin” for a given insurance line. “Ruin” means encountering claims that exhaust initial reserves plus accumulated premiums. …
Which is better - wealth or ability? Fred Mosteller posed this question in his classic 1965 small compendium Fifty Challenging Problems in Probability, in the context of the Gambler’s Ruin puzzle. Two players, M and N, engage in a game in which $1 is transferred…
As the popularity of data science has grown, so too has advice on how to get jobs in data science. A common form of advice is a list of sample questions you might be asked at your job interview (see here and here for examples). …
The Three Stooges comedy sketch “Ants in the Pantry,” (1935), features the Stooges as exterminators whose target customers don’t have enough pests. The Stooges solve the problem by bringing their own pests (ants and mice) on sales calls, and surreptitiously releasing them. Having created the…
“I wouldn’t have said I loved statistics before I started at Statistics.com. But now I do. I really do.” Staci Taylor is an Assistant Professor of Nursing at Southeastern Louisiana State University. She was asked to teach statistics, and signed up with Statistics.com to refresh…
In this feature, we sometimes highlight terms that can have different meanings to different parts of the data science community, or in different contexts. Today’s term is “bias.” To the lay person, and to those worried about the ethical problems sometimes posed by the deployment…
We encountered “Type III error” when it turned out that most people answering our Puzzle question were, in fact, answering a different question from the one that was asked. Type III error is answering the wrong question, and it is a big factor in the…
Late last year, we offered this puzzle, to which no answer was provided at the time: McKinsey recently came out with a study of how a shift to remote learning has affected math test scores of students in elementary school. The impact of school closures…
In this week’s Briefing, we take a look at different strands of “purity” in AI. Our course spotlight is Jan 15 - Feb 12: Introduction to Data Literacy It's for you or anyone you know who needs to get more numerate! See you or them in…
This week we offer a puzzle to which I have no answer. McKinsey recently came out with a study of how a shift to remote learning has affected test scores of students in elementary school. The impact of school closures has been large and negative…
“Extremism in the defense of liberty is no vice. Moderation in the pursuit of justice is no virtue.” So said Barry Goldwater, running for U.S. President in 1964. At the time, the voters rejected his pitch for purity, and his opponent, Lyndon Johnson, won a…
In Natural Language Processing (our course on the subject starts Jan 15), entity extraction is the process of labeling chunks of text as entities (e.g. people or organizations). Consider this phrase from the blog on close elections linked above: “the tie was not between Jefferson…
The recent U.S. election was one of the most controversial and closest ever, and turnout percentage may be the highest in a century. Still, 37% of the voting age population did not vote. The traditional explanation for why people don’t vote is that they feel…
In our Briefing this week, we revisit a topic we looked at a while ago, the epidemiology of gang activity in El Salvador, and look at the impact of Covid. Our spotlight is on: Oct 30 - Nov 27: Sample Size and Power Determination See…
Meet Suma Krishnaprasad Data Scientist, Cleveland Clinic Suma Krishnaprasad was the first data scientist hired at Cleveland Clinic Abu Dhabi. She works to develop and deploy predictive models, and also to provide statistical design and analysis for dozens of clinical trials and other research projects. She…
Dr. Carlos Carcach is Professor & Director of the Center for Public Policy at the Escuela Superior de Economía y Negocios (ESEN) in Santa Tecla, El Salvador, and coordinator of ESEN's post-graduate program in predictive analytics, which offers online instruction in partnership with Statistics.com, using…
Meet Jessica Sproviero,Assistant Vice President at Merrill Financial Services Jessica Sproviero has been working for several years in finance (asst. VP at Merrill Financial Services) while pursuing a degree at Thomas Edison State University (TESU). She entered the data science portion of the program (provided…
In our Briefing this week, we take a look at unemployment insurance fraud and a statistical tool for catching the crooks. Our course spotlight is on: Oct 23 - Nov 20: Spatial Statistics See you in class! Peter Bruce Founder, Author, and Senior Scientist Unemployment…
The worldwide Covid recession has led to a dramatic increase in unemployment and, hence, Unemployment Insurance (UI) claims. The figure below, from the U.S. Dept. of Labor (via https://www.npr.org/2020/03/26/821580191/unemployment-claims-expected-to-shatter-records), shows new claims on a weekly basis. Compare the March Covid-related peak on the right to…
In our Briefing this week, we take a look at the role of statistics and analytics in war, from WWII to the present. Our curriculum spotlight is on our Rasch and IRT Mastery - key skills for those involved in designing, developing, and analyzing tests…
The statistician John Tukey is regarded by some as the father, or at least one of the fathers, of data science. Before Tukey, statistics meant inference (p-values, ANOVA, etc.) and models. Tukey brought to the discipline a whole new perspective: exploring the data to see…
World War 2 gave the statistics profession its big growth spurt. Statistical methods such as correlation, regression, ANOVA, and significance testing were all worked out previously, but it was the war which brought large numbers of people to the field as a profession. They didn’t…
This week we take a look at the interesting statistical problem of false positives, which naturally arise when you do lots of diagnostic tests or hypothesis tests. Our course spotlight deals with another aspect of multiple statistical studies - how to combine them into a…
“A little knowledge is a dangerous thing,” said Alexander Pope in 1711; he could have been speaking of the use of statistics by experts in all fields. In this article, we look at three consequential mistakes in the field of statistics. Two of them are famous, the third required a deep dive into the corporate annual reports of
“A little knowledge is a dangerous thing,” said Alexander Pope in 1711; he could have been speaking of the use of statistics by experts in all fields. In this article, we look at three consequential mistakes in the field of statistics. Two of them are famous, the third required a deep dive into the corporate annual reports of
Several decades ago, the dominant therapies for lung cancer were radiation, which offered better short-term survival rates, and surgery, which offered better long-term rates. A thought experiment was conducted in which surgeons were randomly assigned to one of two groups and asked whether they would choose surgery. Group 1 was told: The one-month survival rate is 90%. Group 2 was told: There is 10% mortality in the first month. Yes, the two statements say the same thing. What did the two physician groups choose?
This week we look at the second most popular percentage in statistics: 80%. Our course spotlight is on: Oct 30 –Nov 27: Sample Size and Power Determination See you in class! Peter Bruce Founder, Author, and Senior Scientist The Popular 80% Researchers and analysts are…
Type I error in statistical analysis is incorrectly rejecting the null hypothesis - being fooled by random chance into thinking something interesting is happening. The arcane machinery of statistical inference - significance testing and confidence intervals - was erected to avoid Type I error. Type II error…
Researchers and analysts are familiar with the famous 5% benchmark in statistics, the typical probability threshold at which a result becomes statistically significant. (The probability in question is the probability that a result as interesting as the real-life result will happen in the null model.) …
This week, our topic is Data Engineering, and we feature a guest blog by Will Goodrum, a data scientist at Elder Research. Our course spotlight is Oct 2 -30: Categorical Data Analysis See you in class! Peter Bruce Founder, Author, and Senior Scientist Four Common…
By Will Goodrum* Note: A version of this article was first published on the Elder Research blog. Your company has made it a strategic priority to become more data-driven. Good! A major anticipated component of this transition is to implement new data technology (e.g., a…
The Relative Risk Ratio and Odds Ratio are both used to measure the medical effect of a treatment or variable to which people are exposed. The effect could be beneficial (from a therapy) or harmful (from a hazard). Risk is the number of those having…
Vaccines for Covid are in the news, and this week we focus on the clinical trial process that validates vaccines as safe and effective. Our spotlight is on our 10-course Biostatistics Certificate Program. You can get started with Jan 3-31: Biostatistics 1 For Medical Science…
An outlier or anomaly is typically defined as a case that is markedly distant or different from the bulk of the data. Our July 28 blog on outliers and anomaly detection reported on one unusual case in which the outlier might lie fully within the…
As of this writing, there are about 40 Coronavirus vaccines in the clinical trial process, plus another 135 in preclinical development. Russia has jumped the gun and “approved” a vaccine that has just begun Phase 3 trials, and, likewise, China has approved a pre-Phase 3…
Last week we looked at a notable failure of the statistic “AUC”; this week we dive deeper. Our curriculum spotlight is our 10-course Analytics for Data Science certificate program: compare cost and coverage to ANY Master’s program! You can get started with Sep 11 – Oct…
By John Elder, Founder and Chair of Elder Research, Inc. Last week, in Recidivism, and the Failure of AUC, we saw how the use of “Area Under the Curve” (AUC) concealed bias against African-Americans defendants in a model predicting recidivism, that is, which defendants would re-offend. …
On average, 40% - 50% of convicted criminals in the U.S. go on to commit another crime (“recidivate”) after they are released. For nearly 20 years, court systems have used statistical and machine learning algorithms to predict the probability of recidivism, and to guide sentencing…
In a randomized experiment, the endpoint or outcome is a formal measure (statistic) of the result of the experiment. In a randomized clinical trial preparatory to regulatory submission, there is often more than one outcome, due to the time and expense involved in conducting a…
In this week’s brief, we feature a data-detective story: The Case of the Faulty Generator. Our spotlight is on our Analytics for Data Science certificate program*. See you in class! *Earn a Bachelor’s Degree in Data Science and Analytics concurrently at Thomas Edison State University.…
In generalized linear models, a link function maps a nonlinear relationship to a linear one so that a linear model can be fit (and then mapped to the original form). For example, in logistic regression, we want to find the probability of success: P(Y =…
Prepared by Peter Bruce, Mark Smith and Ramon Perez, this case study was originally published at elderresearch.com. In early 2020, Sira-Kvina Kraftselskap, a large producer of hydroelectric power in Norway, suffered a breakdownof one of its major generators. Company technicians went through established diagnostics…
In casual statistical analysis, you sometimes hear references to outliers, along with the suggestion that they should be ignored or dropped from the analysis. Quite the contrary: often it is the outliers that convey useful information. They may represent errors in data collection, e.g. a…
In this week’s brief we discuss outliers and anomalies, the unusual cases and events that often end up being the focus of attention. Our course spotlight is Nov 6 - Dec 4: Anomaly Detection If you’re interested in this topic, you should also consider the…
In this mature age of digital marketing, companies have developed finely honed engines of automated and targeted promotion that factor in individual preferences and behavior. The idea is to add small increments to revenue and profit. The system evolved in a stable era of economic…
Myth 1: It’s All About Prediction “Who cares whether we understand the model - as long as it predicts well!” This was one of the seeming benefits of the era of big data and predictive modeling, and it set data science apart from traditional statistics. …
In this week’s brief, a continuation of our “Statistical Thinking” series, we reflect on three “myths” in data science and statistics, and spotlight our ten-course Social Science Statistics certificate program. You can get started with either of these courses: Aug 7- Sep 4: Survey Design and…
As Independence Day inaugurates the official summer political season in the U.S. (a season that, in reality, no longer ends), we discuss in this week’s brief uplift models; our course spotlight is on Aug 21 - Sep 18: Persuasion Analytics and Targeting See you in…
On July 4, 1826, U.S. Independence Day, both John Adams and Thomas Jefferson, the second and third presidents of the U.S., both died within hours of each other. Adams and Jefferson personified opposing factions in U.S. politics, with Adams favoring a strong central government and…
Model interpretability refers to the ability for a human to understand and articulate the relationship between a model’s predictors and its outcome. For linear models, including linear and logistic regression, these relationships are seen directly in the model coefficients. For black-box models like neural nets,…
Ken Strasma is a pioneer in the field of predictive analytics in high-stakes Presidential campaigns, serving as the National Targeting Director for President Obama’s historic 2008 campaign and for John Kerry’s 2004 presidential campaign. He produced the predictive analytics models used by the campaigns, and helped popularize…
In his book Predictive Analytics, Eric Siegel tells the story of marketing efforts at Telenor, a Norwegian telecom, to reduce churn (customers leaving for another carrier). Sophisticated analytics were used to guide the campaigns, but the managers gradually discovered that some campaigns were backfiring: they…
In this week’s Brief, the second in our series on statistical thinking, we discuss WWII convoys; our course spotlight is July 10 - Aug 7: Spatial Statistics for GIS Using R See you in class! Peter Bruce Founder, Author, and Senior Scientist Statistical Thinking 2 Safety…
Statistical Thinking 2: Safety in Numbers – Calculating Probabilities for Convoys Early 1942 was a critical period for the Allies in WWII. Russia was on its heels, with German armies at the gates of Moscow and preparing an offensive in southern Russia. Alone among the…
Polytomous, applied to variables (usually outcome variables), means multi-category (i.e. more than two categories). Synonym: multinomial.
In this week’s Brief, the first in a Statistical Thinking series, we look at how people think about rare events. Our spotlight is on: July 3 - 31: Introductory Statistics (another session starts July 31) See you in class! Peter Bruce Founder, Author, and Senior…
Meet Angelina Salinas, Data Analyst at Almacenes SIMAN Angelina Salinas started working for the retail store Almacenes Siman as a purchasing planner and, a couple of years later, got interested in data science and started to learn R. Shortly afterwards, the business intelligence group at…
Can you identify this wildflower, photographed in a Massachusetts field? And also identify its significance in the history of statistics? This is the Blue Flag Iris, also called the Veriscolor Iris, and it is one of three Iris species that make up the famous (in statistics) Iris…
Statistical Thinking 1 Several years ago, an NPR reporter wanted a comment from me for his story about an unusual event: a woman had won a state lottery jackpot for a second time. Winning once was low enough odds, but winning twice? The reporter found…
In this week’s brief we feature a guest blog on Ethical Data Science; our course spotlight is: July 17 – Aug 14: Logistic Regression See you in class! Peter Bruce Founder, Author, and Senior Scientist Ethical Data Science As data science has evolved into AI,…
Joseph Hilbe, a prolific author in the field of statistical modeling, taught a number of Statistics.com courses right up until his death, in March of 2017. Hilbe was elected as a Fellow of the American Statistical Association; his expertise was in statistical modeling. He did…
Guest Blog - Grant Fleming, Data Scientist, Elder Research Progress in data science is largely driven by the ever-improving predictive performance of increasingly complex black-box models. However, these predictive gains have come at the expense of losing the ability to interpret the relationships derived between…
In this Brief, we visit the issue of “statistical arbitrage” in financial markets, and spotlight two courses: June 12 - July 10: Financial Risk Modeling (today) July 10 - Aug 7: Spatial Statistics for GIS Using R See you in class! P.S. Our newest course,…
An economics professor and an engineering professor were walking across campus. The engineering professor spots something lying in the grass - “Look- here’s a $20 bill!” The economist doesn’t bother to look. “It can’t be - somebody would have picked it up.” This old joke…
Fear of catching Covid-19 dominates the world, so this week we briefly review how humans think about probabilities, in the context of Covid-19. Prior beliefs figure heavily in probability calculations, so our course spotlight is on: July 3 - 31: Introduction to Bayesian Statistics See you…
Bayesian statistics provides probability estimates of the true state of the world. An unremarkable statement, you might think -what else would statistics be for? But classical frequentist statistics, strictly speaking, only provide estimates of the state of a hothouse world, estimates that must be translated…
In 1998, Craig Fox and Amos Tversky reported on a survey in which U.S. basketball fans were asked to judge the probability that each of 8 teams might win the championship. Students of statistics can probably guess the outcome - the probabilities for all the…
Meet Paul Olszlyn, Senior Data Scientist at NovoDynamics Paul Olsztyn designs and implements databases at NovoDynamics, a company that creates and deploys large scale data systems for corporations. As his company responded to customer needs for more predictive analytics by building greater capacity in this…
This week we return to Coronavirus data to look at new analyses that use mobile phone data to estimate the effects of social distancing restrictions, a vital question now are we see the world falling into “lockdown recession.” Speaking of economic matters, our course spotlight…
As Covid-19 continues to spread, so will research on its behavior. Models that rely mainly on time-series data will expand to cover relevant other predictors (covariates), and one such predictor will be gregariousness. How to measure it? In psychology there is the standard personality trait…
A recent development in the modeling of Covid-19 data has been the use of mobile phone location data, now available from Google, to estimate the degree to which social distancing restrictions have been implemented, and the effect they have had. One interesting analysis comes from…
This week we take a look at evolutionary algorithms (it was 150 years ago that Charles Darwin first used the term “evolution” in his writings). Our course spotlight is: July 17 - Aug 14: Optimization with Linear Programming See you in class! - Peter Bruce…
Wayne Folta is a Lead Data Scientist with Elder Research, a leading data science consulting company and the parent of Statistics.com. Wayne’s current ongoing project involves the extraction, analysis and redaction of text. For example, a healthcare organization might need to release records, stripped of…
Parameterized code in computer programs (or visualizations or spreadsheets) is code where the arguments being operated on are defined once as a parameter, at the beginning, so they do not have to be repeatedly explicitly defined in the body of the code. This allows for…
It was 150 years ago when Darwin first used the term “evolution” in his writing (in his book The Descent of Man). Two months ago, in The Normal Share of Paupers, I briefly discussed the unfortunate eugenics baggage that the discipline of statistics inherited from…
Meet Timothy Young, a Contract Administrator for the County of Los Angeles Timothy recently started the Data Science Analytics Bachelor’s Degree program that Statistics.com offers in conjunction with Thomas Edison State University (TESU) and has already been able to put his learning to work. At…
In this Brief, we dive into the terms “sensitivity” and “specificity” and their relatives. In our course spotlight, clinical trials is the topic. Now there’s a site just for the 800+ clinical trials associated with Covid-19 (treatments and vaccines). Is it time for you to…
We defined these terms already (see this blog), but how can you remember which is which, so you don’t have to look them up? If you can remember the order in which to recite them - sensitivity then specificity, it’s easy. Think “positive and negative”…
In this week’s Brief, we look deeper into the question of whether Covid-19 is a senior citizen disease. Our course spotlight is twofold: Start in May or June: Mastery in Statistical Modeling (3 courses) June 12 to July 10 Analyzing and Modeling Covid-19 Data See…
Covid-19 has brought statistical concepts and terms into the news as never before. One confusing tangle is the array of terms surrounding diagnostic test results. The most basic is accuracy - what percent of test results are correct. This is not necessarily the most important…
A decision stump is a decision tree with just one decision, leading to two or more leaves. For example, in this decision stump a borrower score of 0.475 or greater leads to a classification of “loan will default” while a borrower score less than 0.475…
As more information arrives about the Coronavirus, researchers point more and more to airborne particles and aerosols as the mechanism of spread. Photographic images of a sneeze, such as this one from Lydia Bourouiba at MIT (source here), have been seen by many. It turns…
For infectious diseases, R0 (R-nought) is the unimpeded replication rate of the disease pathogen in a naive (not immune) population. An R0 of 2 means that each person with the disease infects two others. Some things to keep in mind: An R0 of one means…
