First of all, let us start with data itself. There are two types of data, and understanding the differences between them and what situations you use them in is critical to your understanding if statistics.
Types of Data:
Quantitative - Numerical values
Categorical (Qualitative) - Non-numerical groupings
Let me give an example of each type of data in a situation. Let's say you are comparing income inequality between genders. In this situation, there would be two variables, the annual income of the individual, and the gender of the individual.
In this situation, the annual income would be quantitative data. One way you can confirm this is that you are able to calculate measurements such as mean and median from this data.
On the other hand, the gender would be categorical. For the sake of this argument, let us say that there are two genders among the individuals measured: male and female. It would be impossible to run calculations such as mean or median on gender, as it is a non-numerical value.
Understanding the difference between quantitative and categorical data will be a crucial fundamental as we explore more complex concepts later on. Here are some exercises that you can try to master your knowledge in this category.
1.) Number of trees planted annually
2.) Temperature in °F
3.) Year (A.D.)
4.) Common names of children
5.) Population of the 10 largest cities in the U.S.
6.) Height (in cm)
7.) Nations in the OECD
8.) Commuting time (in hours)
9.) Hours of sleep
10.) Names of former instructors
