Month: February 2017

Variable Reduction Best Practices

Published February 21, 2017.

Nowadays, in the data mining world, having too much data has become a more prevailing problem than not having enough. Building a predictive model on all available variables can be a time consuming task, one that will take a long time to compute and becomes less robust and harder to interpret. So, what can we […]

Statistical Power

Published February 14, 2017.

Introduction What is statistical power? Sometimes called the sensitivity of a hypothesis test, statistical power describes the ability for a statistical test to identify whether the effect it is trying to find or measure exists or not. If you’re wondering how a test designed to measure a statistical effect might be unable to measure that […]

Data science platforms need to adapt to trends in enterprise IT

Published February 1, 2017.

From simple technologies like emails to sophisticated ones like ERP platforms, the transformation in enterprise IT is undeniable. There are several consistent trends within enterprise IT that would directly impact data scientists. These changes are fairly consistent across industries, which would require data scientists to closely examine their data science platform of choice. Here are […]