The Pearson correlation allow us to find if two variables move together in a straight-line way. For instance if we ought to check the weight of students, we might notice that the same increases alongside the height. Pearson help us to know how strong that straight line relationship is using numbers from -1 to +1. Being +1 positive relationship in which both go up and -1 negative in which one goes up while other goes down. Spearman on the other hand, cheeks if two things are connected, this works with data that is ordinal. So it ranks the values instead of using the exact numbers. Finally, Chi-square test help us to know when two categories are related, for instance the connection between gender and a certain type of music. This method counts how often things happen and if those numbers mean something. When using this test it is important to follow certain assumptions to make sure the results are correct. One of them is normality that determines if the data follows a bell curve shape which means that has a normal distribution. The measurement level tells us what kind of data we have whether it is numbers, ranks or categories. This is important to determine to design the right test. Using the right assumptions helps us keep the results of our study reliable.