• Articles Archive

Advancing the Power of Analytics

Being able to collect, collate and analyze data stored on servers is becoming ever-more critical as companies use this to find insight and improve efficiency and effectiveness. This article written by Minitab Trainer Bruno Scibilia with the contribution of Minitab Sr. Advisory User Experience Designer and Technical Trainer Cheryl Pammer, gives you some insights on the value of Modern Statistics combined with Computer Science. Minitab has acquired Salford Systems, specialized in state-of-the-art machine learning technology designed to assist data scientists in all aspects of predictive model development.

A Statistical Analysis of Boston’s 2015 Record Snowfall

More than 90 inches of snow fell in Boston in the winter of 2015, but how rare was this occurrence? This article explores the rarity of the 2015 Boston snowfall amount in terms of Sigma Levels and examines University of Oklahoma meteorologist Sam Lillo’s estimate of the likelihood of this event occurring.

Using Nonlinear Regression in Minitab to Model Diffusion in a High Intensity Discharge Lamp

Using Nonlinear Regression in Minitab to Model Diffusion in a High Intensity Discharge Lamp By P. Watté, Philips Innovative Applications, Global Technology and Development HID & SL, Belgium Introduction

Teaching DoE with Paper Helicopters and Minitab

Explaining what DOE is and what it can do for you is difficult, but having a paper helicopter on hand helps. The paper helicopter provides a way to quickly explain and understand basic DOE concepts. It also offers an easy-to-do experiment you can analyze with Minitab Statistical Software. This article leads you step-by-step through the creation and analysis of a paper helicopter DOE.

ARIMA: How to Avoid the Herd When Analyzing Time Series Data

Getting the right information out of time series data requires skill and experience, and perhaps inspiration and intuition, too. This article discusses how to analyze time series data using some more sophisticated tools which are often not covered in basic statistical training programs.

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