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.…
Convinced that he, like his father, would die in his 40’s, Winston Churchill lived his early life in a frenetic hurry. He had participated in four wars on three continents by his mid-20’s, served in multiple ministerial positions by his 30’s, and published 12 books…
Are you "young and rustic?" Or perhaps a "toolbelt traditionalist?" These are nicknames given to customer segments identified by market research firm Claritas, with its statistical clustering tool. Long before the advent of individualized product recommendations, business sought to segment customers into distinct groups on…
It is 100 years since R A Fischer introduced the concept of "variance"(in his 1918 paper "The Correlation Between Relatives on the Supposition of Mendelian Inheritance"). There is much that statistics has given us in the century that followed. Randomized clinical trials, and the means to…
Deep learning is essentially "neural networks on steroids" and it lies at the core of the most intriguing and powerful applications of artificial intelligence. Facial recognition (which you encounter daily in Facebook and other social media) harnesses many levels of data science tools, including algorithms…
SEM stands for "structural equation modeling," and we are fortunate to have Prof. Randall Schumacker teaching this subject at Statistics.com. Randy created the Structural Equation Modeling (SEM) journal in 1994 and the Structural Equation Modeling Special Interest Group (SIG) at the American Educational Research Association…
Two important statistical modeling courses are coming up in May. May 18 - Jun 15: Principal Components and Factor Analysis May 18 - Jun 15: Modeling Count Data Factor analysis is used frequently in social science research where you want to examine that which…
Do you work with multiple choice tests, or Likert scale assessment surveys? Rasch methods help you construct linear measures from these forms of scored observations and analyze the results from such surveys and tests. "Practical Rasch Measurement - Core Topics" In this course, you will…
"The customer is always right" was the motto Selfridge's department store coined in 1909. "We'll tell the customer what they want" was Madison Avenue's mantra starting in the 1950's. Now data scientists like Karolis Urbonas help companies like Amazon (where he works in Europe as…
Predicting whether an internet user will click on a link or buy a product, whether an insurance claim is fraudulent, whether a home mortgage will be paid on time (or early), how much a house will sell for, what internet ad you should see next,…
Have you ever needed to analyze data with a spatial component? Geographic clusters of disease, crimes, animals, plants, events?Or describing the spatial variation of something, and perhaps correlating it with some other predictor? Assessing whether the geographic distribution of something departs from randomness? Location data…
The term text mining is sometimes used in two different meanings in computational statistics: Using predictive modeling to label many documents (e.g. legal docs might be "relevant" or "not relevant") - this is what we call text mining. Using grammar and syntax to parse the…
Text analytics or text mining is the natural extension of predictive analytics, and Statistics.com's text analytics program starts Feb. 6. Text analytics is now ubiquitous and yields insight in: Marketing: Voice of the customer, social media analysis, churn analysis, market research, survey analysis Business: Competitive…
Say you operate a tank farm (to store and sell fuel). How much of each fuel grade should you buy? You have specified flow and storage capacities, constraints on what types of fuels can be stored in which tanks, prior contractual obligations about minimum monthly…
Crowdsourcing, using the power of the crowd to solve problems, has been used for many functions and tasks, including predictive modeling (like the 2009 Netflix Contest). Typically, problems are broadcast to an unknown group of statistical modelers on the Internet, and solutions are sought. Every…
