July 7: Statistics in Practice

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…

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Random Chance or Not?

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…

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Model Interpretability

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,…

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Instructor Spotlight: Ken Strasma

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…

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Predicting “Do Not Disturbs”

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…

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June 30: Statistics in Practice

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…

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Polytomous

Polytomous, applied to variables (usually outcome variables), means multi-category (i.e. more than two categories).  Synonym:  multinomial. 

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June 23: Statistics in Practice

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…

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Student Spotlight: Angelina Salinas

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…

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Historical Spotlight: Iris Dataset

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…

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Rare Event Syndrome

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…

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June 16: Statistics in Practice

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,…

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Instructor Spotlight: Joseph Hilbe

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…

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Ethical Data Science

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…

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June 12: Statistics in Practice

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,…

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Statistical Arbitrage

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…

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June 2: Statistics in Practice

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…

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Bayesian Statistics

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…

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When Probabilities Sum to More than One

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…

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Student Spotlight: Paul Olszlyn

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…

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May 26: Statistics in Practice

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…

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Density

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…

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Tracking Your Wanderings, for the Public Good

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…

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May 19: Statistics in Practice

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…

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Instructor Spotlight: Wayne Folta

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…

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Parameterized

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…

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Evolutionary Algorithms

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…

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Student Spotlight: Timothy Young

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…

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May 12: Statistics in Practice

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…

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Sensitivity and Specificity

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”…

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May 5: Statistics in Practice

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…

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COVID-19: Sensitivity, Specificity, and More

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…

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Decision Stumps

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…

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Miasma

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…

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R0 (R-nought)

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…

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Apr 28: Statistics in Practice

Models of virus growth are in the news, and this week we take a closer look at the modeling of epidemics, and introduce our newest course: June 12 to July 10  Analyzing and Modeling Covid-19 Data We’ll cover analysis of covid data broadly, and focus…

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Conversations with Data Scientists about R and Python

Died-in-the-wool software developers can get quite passionate about the relative virtues of one programming language or another, their debates sometimes threatening to transport you back to middle-school arguments about the greatest ballplayers of all time.  Though their computer passions find other outlets as well, data…

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Apr 21: Statistics in Practice

In this week’s Brief we take a look at Python vrs. R, and feature some conversations with data scientists.  Our spotlight is on our introductory statistical programming courses: May 15 - June 12:  Introduction to Python Programming May 15 - June 12:  R Programming Introduction…

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Apr 14: Statistics in Practice

In this week’s Brief, we explore what data on the flu can tell us about Covid-19 counter-measures.  Our course spotlight is July 31 - Sept 25:  Biostatistics See you in class! - Peter Bruce Founder, Author, and Senior Scientist Social Distancing and the Flu The…

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John Snow

John Snow is popularly regarded as the founder of the field of epidemiology, with his famous study of cholera in London.  Snow plotted cholera cases for a neighborhood served by two wells, and found that nearly all clustered around one of the wells, the Broad…

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Apr 7: Statistics in Practice

In this week’s Brief, we look in greater detail at Elder Research, Inc., which recently acquired Statistics.com.  If your organization is like most organizations, your data science initiatives may lack the direction and support they need to succeed - having a data science team does…

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Observation and Quote from John Elder, IV

"The hype around Artificial Intelligence, Machine Learning, and Data Science is enormous, so it’s tempting to be skeptical of the return on investment (ROI) claimed. Still, most of the results are real. Organizations may suspect there is value in their data assets but not be…

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Elder Research Capabilities

In late December, Statistics.com was acquired by Elder Research, Inc. Many of you have asked for more detail, so here’s an introduction to the folks at Elder Research and some stories of what they do.  There are 100+ employees at Elder Research, led by John…

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Apr 2: Statistics in Practice – Special Epi Course

In this special Brief we step back and look at various estimates of the projected death toll from the coronavirus.   Would you like to learn more about the statistical analysis of disease?  We’re offering a special self-paced course to those seeking to improve their knowledge…

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Coronavirus Death Toll

There are tens of thousands of epidemiologists the world over, and we are beginning to see a bumper crop of forecasts for the ultimate 2020 death toll from Covid-19.  It’s a grim but important forecasting task. Most citizens would support draconian measures to prevent deaths…

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Mar 31: Statistics in Practice

In this week’s Brief, we look at p-values.  Plus, we’ve scheduled a couple of extra course sessions for April:  Use the month of April to introduce yourself to Python, or, for those with some Python familiarity, learn how to apply it to predictive analytics. April…

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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…

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The Depression Gene

The risks of large-scale testing, and the potential for false discovery, can be seen in the “discovery” of the genetic basis for anxiety and depression.  Specifically, serotonin transporter gene 5-HTTLPR. Color Genomics sells a genetic testing product that supposedly can predict which anti-depressant drug works…

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Hazard

In biostatistics, hazard, or the hazard rate, is the instantaneous rate of an event (death, failure…).  It is the probability of the event occurring in a (vanishingly) small period of time, divided by the amount of time (mathematically it is the limit of this quantity…

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Mar 24: Statistics in Practice

In this week’s Brief, we look again at the statistics of Coronavirus.  We also spotlight our Health Analytics Mastery - a 3-course series in which you can choose from among Biostatistics 1 and 2 Designing Valid Statistical Studies Epidemiologic Statistics * Introduction to Statistical Issues…

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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…

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Preliminary Paper

Here is a preliminary paper that suggests that RNA extraction kits, one of the main bottlenecks to Covid-19 testing in the US, can be skipped altogether and the next part of the assay (RT-qPCR) still works.  If confirmed, this result would have a major impact…

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Mar 18: Statistics in Practice

In this week’s Brief, we look at the coronavirus, and the problem of estimating prevalence and mortality.  Our course spotlight is Nov 8 - Dec 6:  Epidemiologic Statistics (we're adding a spring session - email us to be notified when registration opens at ourcourses@statistics.com) See…

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Standardized Death Rate

Often the death rate for a disease is fully known only for a group where the disease has been well studied.  For example, the 3711 passengers on the Diamond Princess cruise ship are, to date, the most fully studied coronavirus population.  All passengers were tested…

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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…

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Coronavirus: To Test or Not to Test

In recent years, under the influence of statisticians, the medical profession has dialed back on screening tests.  With relatively rare conditions, widespread testing yields many false positives and doctor visits, whose collective cost can outweigh benefits.  Coronavirus advice follows this line - testing is limited…

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Mar 16: Statistics in Practice

In this week’s Brief, we look at combining models.  Our course spotlight is April 17 - May 1:  Maximum Likelihood Estimation (MLE) You’ve probably seen lots of references to MLE in other contexts - this quick 2-week course (only $299) is your chance to study…

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Regularized Model

In building statistical and machine learning models, regularization is the addition of penalty terms to predictor coefficients to discourage complex models that would otherwise overfit the data.  An example is ridge regression.

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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…

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Mar 9: Statistics in Practice

In this week’s Brief, we look at ways to determine optimal sample size.  Our course spotlight is April 10 - May 8:  Sample Size and Power Determination See you in class! - Peter Bruce Founder, Author, and Senior Scientist Big Sample, Unreliable Result The 1948…

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Ridge Regression

Ridge regression is a method of penalizing coefficients in a regression model to force a more parsimonious model (one with fewer predictors) than would be produced by an ordinary least squares model. The term “ridge” was applied by Arthur Hoerl in 1970, who saw similarities…

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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…

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Mar 2: Statistics in Practice

In this week’s Brief, we look at hierarchical and mixed models.  Our course spotlight is April 10 - May 8:  Generalized Linear Models April 24 - May 22:  Mixed and Hierarchical Linear Models See you in class! - Peter Bruce Founder, Author, and Senior Scientist…

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Problem of the Week: Notify or Don’t Notify?

Our problem of the week is an ethical dilemma, posed by the New England Journal of Medicine to its readers 10 days ago.  Volunteers contributed DNA samples to investigators building a genetic database for study, on condition the data would be deidentified and kept confidential…

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Factor

The term “factor” has different meanings in statistics that can be confusing because they conflict.   In statistical programming languages like R, factor acts as an adjective, used synonymously with categorical - a factor variable is the same thing as a categorical variable.  These factor variables…

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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…

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Feb 24: Statistics in Practice

In this week’s Brief, we look at social categories, and the role that statistics and data science have played in social engineering - 100 years ago and today.  Our course spotlight is April 3 - May 1:  Categorical Data Analysis See you in class! -…

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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…

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Purity

In classification, purity measures the extent to which a group of records share the same class.  It is also termed class purity or homogeneity, and sometimes impurity is measured instead.  The measure Gini impurity, for example, is calculated for a two-class case as p(1-p), where…

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Predictor P-Values in Predictive Modeling

Not So Useful Predictor p-values in linear models are a guide to the statistical significance of a predictor coefficient value - they measure the probability that a randomly shuffled model could have produced a coefficient as great as the fitted value.  They are of limited…

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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…

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Feb 17: Statistics in Practice

Last week we looked at several metrics for assessing the performance of classification models - accuracy, receiver operating characteristics (ROC) curves, and lift (gains).  In this week’s Brief we move beyond lift and cover uplift. Our course spotlight again is: Feb 28 - Mar 27:…

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ROC, Lift and Gains Curves

There are various metrics for assessing the performance of a classification model.  It matters which one you use. The simplest is accuracy - the proportion of cases correctly classified.  In classification tasks where the outcome of interest (“1”) is rare, though, accuracy as a metric…

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Feb 10: Statistics in Practice

Tomorrow is the New Hampshire political primary in the US, and this week’s Brief looks at the statistical concept of lift.  Our spotlight is on: Feb 28 - Mar 27:   Persuasion Analytics and Targeting See you in class! - Peter Bruce, Founder Lift and…

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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…

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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…

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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…

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Feb 3: Statistics in Practice

In this week’s blog, we discuss our recent acquisition by Elder Research Inc. We also look at the “Canary Trap” and its connection to text mining. Our course spotlight is on Jan 31 to Feb 28: Text Mining using Python (still open for registrations, first…

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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,…

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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…

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Book Review: Mining Your Own Business by Gerhard Pilcher and Jeff Deal

This is a short book, Mining Your Own Business: A Primer for Executives on Understanding and Employing Data Mining and  Predictive Analytics" befitting its intended audience - managers and executives with responsibility for data science and analytics projects.  It outlines the requirements for success - not technical model…

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Jan 29: Statistics in Practice + Announcement

This week we discuss the importance of choosing the right analytics problem, with a guest blog from Elder Research, Inc., a data science and analytics consulting and training company, with whom we have just joined forces.   Our course spotlight is on: Feb 14 - Mar 13:  Design…

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Jan 20: Statistics in Practice

This week’s Brief takes a look at ethical dilemmas in data science.  Our course spotlight is on  Feb 21 - Mar 20:  Network Analysis See you in class! - Peter Bruce, Founder and President The Institute for Statistics Education at Statistics.com Ethical Dilemmas in Data…

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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…

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Kernel function

In a standard linear regression, a model is fit to a set of data (the training data); the same linear model applies to all the data.  In local regression methods, multiple models are fit to different neighborhoods of the data. A kernel function is used…

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Jan 13: Statistics in Practice

        In this Brief, we look at prosaic, but lucrative applications of predictive analytics and forecasting to the automotive industry.  Our spotlight is on our 3-course Predictive Analytics Mastery Series. Start this week with: Jan. 10 - Feb 7:   Predictive Analytics…

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Industry Spotlight: Clinical Trials

 “Complete Your Clinical Trial With Our File Data” Clinical trials that support new drug development can cost over a billion dollars.  A new industry has popped up - data collectors and aggregators that provide digital data from their files as evidence in pharmaceutical clinical trials.…

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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. …

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Jan 6: Statistics in Practice

Happy New Year! We are grateful for your continued support and appreciate your interest in learning more about statistics, analytics, and data science. In this new year, think of your learning as an investment both in the future of your company and your career. Below are courses, certificates, and…

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Dec 30: Statistics in Practice

In this Brief, we take a look at the use of simulations as a tool to help sales people with a complex sale (high value, multiple aspects to consider).  Our spotlight is on the 3-course Mastery Series in Optimization Research, which starts January 10 with:…

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Historical Spotlight: Statistical Analysis and Human Rights

Artificial intelligence and analytics have gotten some bad press recently, from the role that social media has played in fracturing and heightening divisions in democratic society to the “big brother” role that data mining and image recognition have played in China’s suppression of minorities.  But…

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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…

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Historical Spotlight: Bell Labs and Statistics

95 years ago, Bell Labs was founded as a joint project of AT&T and Western Electric.  Its primary mission was R&D for its parents’ fast-growing telecommunications businesses.  Since that time, Bell Labs became a fabled American research institution, but also suffered the vicissitudes of trying…

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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…

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Dec 16: Statistics in Practice

In 2005, the cardboard box was inducted into the National Toy Hall of Fame (along with Candy Land). In our brief this week we consider whether analytics has anything to say about cardboard boxes. Our course spotlight is on: Jan 3 - 31:  R Programming…

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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…

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Problem of the Week: A betting puzzle

QUESTION: A gambler playing against the “house” in a game like roulette or slots adopts the rule “Play until you win a certain amount, then stop.”  Will this ensure against player losses? What will be its effect on the house’s profit? ANSWER: Some look at this…

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Book Review: Big Data in Practice by Bernard Marr 

This short book is essentially an enriched list of 45 examples of how companies have used big data analytics.  Marr sticks to high level generalities, and the book is in the spirit of light business journalism rather than detailed expositions that walk you through a…

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Dec 6: Statistics in Practice

This week we look at the casino business - in particular, the odds on slots. In our course spotlight, we start looking at some of the great stuff starting in at the beginning of the new year. In January, you can get started with basic statistics or biostatistics,…

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