The easiest way to understand the difference between permutations and combinations is to realize that the inventor of the “combination lock” named it completely wrong. If your gym locker code is 1-2-3, entering 3-2-1 won’t open it. The order of…
In this module, we have spent a lot of time talking about the Normal Distribution. We learned how the Empirical Rule (68-95-99.7) allows us to predict data perfectly, and how Z-Scores allow us to standardise it. But there is a…
In the last lesson, we learned that if data follows a Normal Distribution, we can use the Empirical Rule (68-95-99.7) to instantly understand exactly where a data point falls compared to the rest of the group. But there is a…
In Descriptive Statistics (Path 2), we acted as historians. We took a dataset that already existed, measured its centre, found its spread, and described its shape. But data scientists rarely get paid to just describe the past. They get paid…
In our last lesson, we looked at the probability of single, isolated events—flipping a coin, clicking an ad, or a server going offline. But what happens when you zoom out? What happens when you plot thousands, or even millions, of…
Imagine you go to the doctor for a routine checkup. The doctor decides to test you for a rare disease that affects 1 in 1,000 people. A few days later, the doctor calls you with terrible news: You tested positive.…
If you roll a die 10,000 times, plot the results on a graph, and squint, you will see a shape. If you measure the heights of 10,000 adult men and plot them, you will see a completely different shape. In…
If you want to understand probability, you have to stop thinking of it as math and start thinking of it as a language. When you translate real-world problems into probability, the entire equation usually hinges on just two words: AND…