This rubric covers the use of statistical tools working on large datasets to create models and derive inferences, as well as coverage of the field in its entirety. This differs from machine learning primarily in that the latter focuses on functional gradient analysis or neural networks (kernels) to derive models.
by Mike Thurber, Principal Scientist, Elder Research Three weeks ago, our Brief Is the Spread of the COVID-19 Coronavirus Being Slowed looked at the impact… Read More »COVID-19 Social Distancing Has Mitigated 2020 Flu Season
by Mike Thurber, Principal Scientist, Elder Research A key issue for COVID-19 response policies moving forward is the asymptomatic rate – people who have the… Read More »COVID-19 Asymptomatic Rates and Implications
by Peter Bruce, President & Founder, Statistics.com Nearly everyone is now familiar with the IHME Covid-19 forecasts (also called the “Murray” model after the lead… Read More »Covid-19: Epidemiological Models vs. Statistical Models
by Mike Thurber, Principal Scientist, Elder Research The COVID-19 pandemic has created a need for clear and actionable analytics like never before. The world can’t… Read More »Is the Spread of the COVID-19 Coronavirus Being Slowed?
Process mining is changing the way enterprises operate and manage their processes. It tells the process ‘as-is’ and ensures that enterprises and process owners have… Read More »Evolution Of Process Mining: A Look At The History
There are a few key differences between the Binomial, Poisson and Hypergeometric Distributions. These distributions are used in data science anywhere there are dichotomous variables (like yes/no, pass/fail). This… Read More »Difference between Binomial, Poisson and Hypergeometric Distribution in One Picture
One of the best-known books on statistics is now free Larry Wasserman’s All of Statistics is free to download from Springer I like this book… Read More »Free book on Statistics: Larry Wasserman’s All of Statistics