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: Jan 10 – Feb 7: Optimization with Linear Programming SeeContinue reading “Dec 30: Statistics in Practice”
Yearly Archives: 2019
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 statistical analysis has also long played a role in documenting,Continue reading “Historical Spotlight: Statistical Analysis and Human Rights”
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 to show components of value such as cost savings orContinue reading “Simulating the Complex Sale”
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 to reconcile its orientation to basic research with the needsContinue reading “Historical Spotlight: Bell Labs and Statistics”
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 box of wine, and dealing with the protective spacers andContinue reading “Analytics Meets the Cardboard Box”
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 Advanced Jan 24 – Feb 21: Visualization in R withContinue reading “Dec 16: Statistics in Practice”
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 friend. Able to run 24/7 with consistently-sized bets, slots realizeContinue reading “Detecting a Slots Payout Difference of 2%”
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 rule and figure that it rules out player losses andContinue reading “Problem of the Week: A betting puzzle”
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 successful big data implementation in detail. However, private companies, andContinue reading “Book Review: Big Data in Practice by Bernard Marr “
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, start our certificate program or degree programs in analytics, get introduced to R programming or PythonContinue reading “Dec 6: Statistics in Practice”
Google Zooms Out on Microtargeting
Google recently announced that it would further limit its election ads to audience targeting based on age, gender, and general location (postal code level) context targeting (i.e. showing ads based on the content being viewed) Up to this point, the application of predictive modeling to “microtarget” individuals or small groups of individuals, well-entrenched in theContinue reading “Google Zooms Out on Microtargeting”
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 games. Pascal’s ensuing work is regarded as the foundation ofContinue reading “Betting and Statistics”
Operations Research (O/R) For Sewage
Older urban sewer systems are not sealed, dedicated route networks leading to sewage treatment plants. Rather, to save money when they were built decades ago, in some places they shared pipes with storm water drainage systems that lead to creeks, rivers and bays. As a result, when stormwater inundates the system, it carries with itContinue reading “Operations Research (O/R) For Sewage”
Nov 25: Statistics in Practice
In this week’s Brief, we take a look at the history of betting and how it is entwined with probabilistic decision-making. Probabilistic decision-making is also the focus of our 3-course Optimization Mastery, which covers linear programming, integer programming, simulation and other operations research (O/R) techniques. Start with: Jan 3 – 31: Optimization – Linear Programming See youContinue reading “Nov 25: Statistics in Practice”
Errors and Loss
Errors – differences between predicted values and actual values, also called residuals – are a key part of statistical models. They form the raw material for various metrics of predictive model performance (accuracy, precision, recall, lift, etc.), and also the basis for diagnostics on descriptive models. A related concept is loss, which is some functionContinue reading “Errors and Loss”
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 we look at some notable examples of unforeseen consequences ofContinue reading “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 creates an expanding set of terms (including some buzzwords) usedContinue reading “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. →Test Yourself Take a 10-question quiz on analytics Data PrepContinue reading “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. Psychologically, they think that an outcome opposite to the streakContinue reading “Statistical Thinking”
Latin hypercube
In Monte Carlo sampling for simulation problems, random values are generated from a probability distribution deemed appropriate for a given scenario (uniform, poisson, exponential, etc.). In simple random sampling, each potential random value within the probability distribution has an equal value of being selected. Just due to the vagaries of random chance, clusters of similarContinue reading “Latin hypercube”