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 …

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, …

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 …

Data Visualization for Product Managers

A few Rules of Thumb to Make You Dangerous Chances are if you’re reading this is you’re a product manager or in some way a contributor to a product team and would like to give yourself a leg up when it comes to understanding the data that is coming your way. I’m going to give …

Three Key Charts for Visualizing Proportion Data

Proportion data examples Whatever your application of data analytics & data science, there are proportions everywhere. Proportions are all about understanding the different parts that make up a whole. Proportions are pretty much just a count of something across a given categorical variable. That could be number of customers across different industries, number of sales …

Getting Started with Experimental Design in R

This quick blog is designed to help you get off to the races quickly in world of data science; and here specifically, Experimental design. Enjoy! When it comes to experiemental design there are three main streps it can be broken down to: PlanningDesignAnalysis Planning & Design Planning should always begin with a well formed hypothesis. …

Principal Component Analysis in R

Hi there! Welcome to my blog on pricipal component analysis in R. Purpose: PCA is a dimensionality rediction technique; meaning that each additional variable you’re including in your modeling process represents a dimension. What does it do?: In terms of what PCA actually does, it takes a dataset with high dimensionality, and reduces them down …

Rules of Thumb for Getting Started with Data Visualization

Intro: Whether you’re trying to break into the world of data analytics or data science, if you’re a product manager, sales leader, or anybody seeking to understand their business being able to utilize data in a meaningful way is key. Whether you’re using data visualization software like Tableau, Domo, PowerBI, etc. or you’re using a …