Understand the Internet’s Relevance Metric in a Hurry: TF-IDF

intro With roots in the 1950’s, TF-IDF is a cornerstone for modern applications determining the relevance of each word in a document. At first glance, one could take the simple approach of looking at volume alone, i.e. “how many times did each term show up?”; but TF-IDF takes us a big step further; not only …

Making Sense of Text in a Hurry: A Regular Expressions Primer

Photo by Dinnow (Pexels.com) Introduction Whether you are brand new to regex and have text data you’d like to make sense of, or you have experience laboring over stack overflow questions hoping to find the exact same use case without quite understanding the jumble of regex you’re putting into use; this introduction will prove a …

Simulating Probability in R: The Classic Monty Hall Problem

Image by Arek Socha from Pixabay  Introduction Over the course of this post, we’re going to learn about using simulation to understand probability and we’ll use the classic example of the Monty Hall gameshow problem. Monty Hall had a gameshow back in the day, where he showcased the following problem. If you’re not familiar with him or they …

Statistical Significance Versus Random Chance: The Intuitive Explanation of P-value

Image by Greg Montani from Pixabay  Introduction Welcome to this lesson on calculating p-values. Before we jump into how to calculate a p-value, it’s important to think about what the p-value is really for. Hypothesis Testing Refresher Without going into too much detail for this post, when establishing a hypothesis test, you will determine a null hypothesis. Your …

Linear Regression Simulation to Understand Slope Sensitivity

Introduction Over the next few minutes, I’ll send you on your way to leveraging linear regression for a bit more than explanation or prediction, rather you’ll utilize them to for the sake of inference. We will leverage simulation for inference in three ways: Understanding model sensitivityp-valueconfidence intervals In this post, we’ll mostly be exploring the …

Understand Customer Churn With The Chi-squared Test Statistic

Introduction The chi-square statistic is a useful tool for understanding the relationship between two categorical variables. For the sake of example, let’s say you work for a tech company that has rolled out a new product and you want to assess the relationship between this product and customer churn. In the age of data, tech …

How to Visualize Multiple Regression in 3D

Image by Mediamodifier from Pixabay Introduction No matter your exposure to data science & the world of statistics, at the very least, you’ve very likely heard of regression. In this post we’ll be talking about multiple regression, as a precursor, you’ll definitely want some familiarity with simple linear regression. If you aren’t familiar you can start here! Otherwise, …

Visualizing Multiple Linear Regression with Heatmaps

Image by DavidRockDesign from Pixabay  Introduction No matter your exposure to data science & the world of statistics, it’s likely that at some point, you’ve at the very least heard of regression. As a precursor to this quick lesson on multiple regression, you should have some familiarity with simple linear regression. If you aren’t, you can start here! …

The Intuitive Explanation of Logistic Regression

Introduction Logistic regression can be pretty difficult to understand! As such I’ve put together a very intuitive explanation of the why, what, and how of logistic regression. We’ll start with some building blocks that should lend well to clearer understanding so hang in there! Through the course of the post, I hope to send you …

Multiple Regression in R

Introduction No matter your exposure to data science & the world of statistics, it’s likely that at some point, you’ve at the very least heard of regression. As a precursor to this quick lesson on multiple regression, you should have some familiarity with simple linear regression. If you aren’t, you can start here! Otherwise let’s …