# Tag: Statistical Significance (4)

**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.

Tags: 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.

Tags: 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.

Tags: 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.

Tags: Classifier, Cross-validation, Model Performance, Statistical Significance