**Null Hypothesis Significance Testing is Still Useful** - Jan 25, 2021.

Even in the aftermath of the replication crisis, statistical significance lingers as an important concept for Data Scientists to understand.

Hypothesis Testing, P-value, Statistical Significance, Statistics

**Demystifying Statistical Significance** - Jul 17, 2020.

With more professionals from a wide range of less technical fields diving into statistical analysis and data modeling, these experimental techniques can seem daunting. To help with these hurdles, this article clarifies some misconceptions around p-values, hypothesis testing, and statistical significance.

P-value, Statistical Significance, Statistics

**Comparing Machine Learning Models: Statistical vs. Practical Significance** - Jan 18, 2019.

Is model A or B more accurate? Hmm… In this blog post, I’d love to share my recent findings on model comparison.

Machine Learning, Model Performance, P-value, Statistical Modeling, Statistical Significance

**How to Compute the Statistical Significance of Two Classifiers Performance Difference** - Mar 30, 2016.

To determine whether a result is statistically significant, a researcher would have to calculate a p-value, which is the probability of observing an effect given that the null hypothesis is true. Here we are demonstrating how you can compute difference between two models using it.

Classifier, Cross-validation, Model Performance, Statistical Significance