While you’re probably much more familiar with the Student’s t-test (independent t-test), there is another t-test that doesn’t get nearly enough credit. The Welch’s t-test is a test that you need in your toolbox if you want to succeed as…
Normality has been shown to help provide more stable machine learning models and improve the accuracy of these models in the long term. The problem is everyone is using their power transformer wrong. This 2-minute guide will show you how…
Natural Language Processing is a cornerstone of data science. With so many different tools out there, sometimes it’s easy to get a bit confused. One thing many data scientists (including me) mess up on is the differences between the CountVectorizer…
As its names suggest, “outliers” refers to a group or singular piece of information that doesn’t seem to fit in with the other information. Our job as data scientists is to identify and deal with these potential outliers. In this…
We’ve all been there; you’ve worked night and day to finally get an accurate model for your dataset. You’ve finally got an output from your model – but it’s scaled. What do you do? How do you reverse standardization? In…
As data scientists, you’ll often face datasets too large to understand. With the recent advances in machine learning, we can visualize nearly any variable, parse massive amounts of text into understandable pieces and find hidden trends within our datasets. After…
When it comes to classification problems, your population data is critical. While investigating our target class, we often notice disproportionate sampling. In these instances, what do we do? The Stratified sampling technique means that your sample data will have the…
In data science, some underlying assumptions are made when you use specific machine learning models. Many of these assumptions are based on the distributions of your data. With this 5-minute read, we will explore how to find the current distributions…
Correlation seems simple on the surface. As one thing gets larger, something either gets larger or smaller. While at a high level, this is generally true, once we go further into correlation, there is much more it can tell us.…
While chi-square tests are very powerful, they are often misused. This hypothesis test is commonly used to test three different things. Chi-Square Goodness of Fit Test Used to test if a categorical variable is from a distribution Chi-Square Test of…