This week we look at several ways to fool yourself, statistically – variants of the “Gambler’s Fallacy.” Gambling is all about accurately assessing risk, so, naturally, our featured course is: Nov 15 – Dec 13: Risk Simulation and Queuing See you in class! – Peter Bruce, Chief Academic Officer, Author, Instructor, and Founder The Institute forContinue reading “Oct 14: Statistics in Practice”
Yearly Archives: 2019
Workforce Management
Anyone who has worked in retail knows the anxiety that attends workforce scheduling for both manager and employee. The manager wonders “Will my employees show up at the right times?” The employee wonders “Will I be scheduled for inconvenient times? Enough hours? Too many hours?” The ability of Uber and Lyft to attract drivers, despiteContinue reading “Workforce Management”
Regularize
The art of statistics and data science lies, in part, in taking a real-world problem and converting it into a well-defined quantitative problem amenable to useful solution. At the technical end of things lies regularization. In data science this involves various methods of simplifying models, to minimize overfitting and better reveal underlying phenomena. Some examplesContinue reading “Regularize”
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 countries governing bias in employment. The total cost of recruiting,Continue reading “Machine Learning and Human Bias”
Oct 7: Statistics in Practice
This week we take a look at how AI encodes human bias, despite our best efforts. Our spotlight this week is on: Nov 8 – Dec 6: Deep Learning See you in class! – Peter Bruce, Chief Academic Officer, Author, Instructor, and Founder The Institute for Statistics Education at Statistics.com Machine Learning and Human Bias DoesContinue reading “Oct 7: Statistics in Practice”
The Curse of Dimensionality
There are more than 3 dozen curses in Harry Potter. Data scientists have only one – the “curse of dimensionality.” Dimensionality is the number of predictors or input variables in a model, and the “curse” refers to the problems that result from including too many features (predictor variables) in a model. Old curses are awakenedContinue reading “The Curse of Dimensionality”
Student Spotlight: Peter Mulready
Peter Mulready is an independent consultant, who worked previously as a system architect at Boehringer Ingelheim, one of the world’s largest pharmaceutical companies. Peter got his degree in biology, but his focus shifted to managing and optimizing the use of data in drug discovery research. Specifically, he lead the information technology team responsible for managingContinue reading “Student Spotlight: Peter Mulready”
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 of passengers and baggage by low-paid workers. It also usesContinue reading “Anomaly Detection via Conversation: “How was your vacation?””
e-cigarettes
Last week, the Trump administration announced a forthcoming ban on e-cigarettes, following news stories of a spate of deaths from vaping. The Wall Street Journal, on Friday the 13th, published both an editorial and an op-ed piece suggesting that any harm from e-cigarettes is minor and unproven, and counterbalanced by the good they do inContinue reading “e-cigarettes”
Book Review: Bandit Algorithms for Website Optimization, by John Myles White
Bandit Algorithms for Website Optimization, by John Myles White A classic statistical experimental design comparing treatments (two treatments, treatment versus control, multiple treatments) specifies a sample size, collection of data, then a decision, typically based on hypothesis-testing: the winning treatment must attain a level of statistical significance, otherwise you go with the default “null hypothesis.”Continue reading “Book Review: Bandit Algorithms for Website Optimization, by John Myles White”
“Islands in Search of Contents”
“Islands in Search of Continents” is the subtitle of an article by Michael Clarke and Iain Chalmers in the Journal of the American Medical Association (1998; 280: 280-282). It refers to the fact that many studies are conducted and reported in isolation from other studies on the same subject. A good review of the subject can beContinue reading ““Islands in Search of Contents””
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 of whether e-cigarettes help you quit smoking – 38 studies Continue reading “Meta Analysis”
Industry Spotlight: Health Analytics
Patient Data Management Health analytics is a hot topic now, but to do the analytics you need data – this is where Electronic Health Records (EHR) come in. An integrated, standardized system for sharing and accessing health data has been “just around the corner” now for more than a decade. Despite a big push byContinue reading “Industry Spotlight: Health Analytics”
Superusers
“Superusers” of medical services are the small fraction of patients that account for huge consumption of medical services. An article published August 14, 2019 in JAMA Surgery (online) reports on the application of machine learning methods to Medicare data on 1,049,160 Medicare patients who underwent surgery, and were then tracked over the next year to assessContinue reading “Superusers”
Job Spotlight: Biostatisticans
Biostatisticians are the shepherds (and the police) that guide the science of developing new therapies for disease. They come in several different flavors: Those involved in gathering information, designing experiments and analyzing data at the drug discovery stage – trying to sort out what works and what doesn’t, and learning which research directions have potentialContinue reading “Job Spotlight: Biostatisticans”
Aug 16: Statistics in Practice
Here in Part 2 of the Weekly Brief, we offer some tools to help you with the question, “what is the optimal set of alternatives to offer consumers?” Our course spotlight is on: Aug 30 – Sep 27: Discrete Choice Modeling and Conjoint Analysis See you in class! – Peter Bruce, Chief Academic Officer, Author, Instructor, andContinue reading “Aug 16: Statistics in Practice”
Problem of the Week: The Second Heads
QUESTION: A friend tosses two coins, and you ask “Is one of them a heads?” The friend replies “Yes.” What is the probability that the other is a heads? ANSWER: One-third. There are four ways the coins could have landed originally: HH: 0.25 probability HT 0.25 probability TH 0.25 probability TT Continue reading “Problem of the Week: The Second Heads”
Aug 13: Statistics in Practice
This week we discuss the distinction between explanatory and predictive modeling and spotlight the workhorses of statistical modeling: Oct 4 – Nov 1: Regression Analysis Oct 4 – Nov 1: Categorical Data Analysis See you in class! – Peter Bruce, Chief Academic Officer, Author, Instructor, and Founder The Institute for Statistics Education at Statistics.com Explain or Predict? Are you flummoxed by the profusion ofContinue reading “Aug 13: Statistics in Practice”
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 linear regression output will contain, in addition to a distributionContinue reading “Explain or Predict?”