Stephanie Glen

There’s no doubt about it, probability and statistics is an enormous field, encompassing topics from the familiar (like the average) to the complex (regression analysis,… Read More »Statistics for Data Science in One Picture

With a ROC curve, you’re trying to find a good model that optimizes the trade off between the False Positive Rate (FPR) and True Positive Rate… Read More »ROC Curve Explained in One Picture

ANOVA is a test to see if there are differences between groups. Put simply, “One-way” or “two-way” refers to the number of independent variables (IVs) in your… Read More »One Way vs Two Way ANOVA + Factorial ANOVA: A Comparison in one Picture

This simple picture shows the differences between descriptive statistics and Inferential statistics.  More information about Descriptive and Inferential Statistics: What is “Descriptive Statistics”? What is… Read More »Descriptive vs. Inferential Statistics in One Picture

The following picture shows the differences between the Z Test and T Test. Not sure which one to use? Find out more here: T-Score vs. Z-Score.

The basic idea behind regression analysis is to take a set of data and use that data to make predictions. A useful first step is to… Read More »Regression Analysis in One Picture

Decision Trees, Random Forests and Boosting are among the top 16 data science and machine learning tools used by data scientists. The three methods are similar,… Read More »Decision Tree vs Random Forest vs Gradient Boosting Machines: Explained Simply

In part 1, I compared a few model evaluation techniques that fall under the umbrella of ‘general statistical tools and tests’. Here in Part 2 I… Read More »Comparing Model Evaluation Techniques Part 2: Classification and Clustering