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 […]
Author Archives: lessonsindatascience
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 […]
Leverage Anti-joins
Introduction Assuming you already have some background with the other more common types of joins, inner, left, right, and outer; adding semi and anti can prove incredibly useful saving you what could have alternatively taken multiple steps. In a previous post, I outlined the benefits of semi-joins and how to use them. Here I’ll be […]
Getting Started with Data Science
Introduction When it comes to getting started in data science it can be a bit overwhelming. You need to know statistics, programming, machine learning… within each of those domains there are a many, many sub domains that can dominate a person’s focus and once they’re done reading everything there is to know about one thing, […]
Leverage Semi-joins in R
Introduction Assuming you already have some background with the other more common types of joins, inner, left, right, and outer; adding semi and anti can prove incredibly useful saving you what could have alternatively taken multiple steps. In this post, I’ll be focusing on just semi-joins; with that said, there is a lot of overlap […]
