If you have followed this learning path from the beginning, you now have a powerful descriptive toolkit. You know how to find the center of your data (Mean, Median), you know how to measure the chaos (Standard Deviation), and you…
So far in this module, we have learned how to find the center of our data (Mean, Median, Mode) and how to measure its overall spread (Variance and Standard Deviation). But sometimes, looking at the entire dataset at once isn’t…
In the last lesson, we learned how to find the exact center of our data using the Mean, Median, and Mode. But knowing the centre only tells you half the story. Imagine you are choosing a city to move to,…
Karl Pearson’s Coefficient of Correlation (r) is one of the first statistics we learn because the output is so simple: a single number between -1 and 1. But that simplicity is a trap. If you feed Pearson’s formula the wrong…
You now know the language of statistics. You know how to identify variables, and you know how to classify your data using the NOIR framework. But all of that knowledge is useless if you don’t have any actual numbers to…
Everyone knows the golden rule of statistics: Correlation does not equal causation. Just because two things move together doesn’t mean one causes the other. Ice cream sales and shark attacks both spike in July, but eating a cone of vanilla…
Congratulations! You have completed the Fundamentals module. You now know how to speak the language of data. You can identify exactly what type of variables you are working with, classify them using the NOIR framework, and recognize the dangerous biases…
In Lesson 2, we learned that data comes in two main flavors: Qualitative (words/categories) and Quantitative (numbers). But in the 1940s, a psychologist named Stanley Smith Stevens realised that this simple split wasn’t enough. He noticed that even within “numbers,”…
In the previous lesson, we learned that data comes in different shapes and sizes—from qualitative categories to quantitative numbers. But in statistics, data rarely sits alone in an empty room. We gather data because we want to see how one…
In statistics, data is our raw material. But just like a chef can’t treat a piece of chicken the same way they treat a carrot, a statistician cannot treat all data the same way. If you try to calculate the…