There are two different things you'll need to know:
Types of Data
1. Categorical
For example, favourite colour, brand of toothpaste you use, brand names, words, etc.
2. Numerical
There are two types of numerical data:
A: Continuous, like a person's height, weight, body temperature, etc.
B: Discrete, like the number of cars in your family, the number of children in your house, the number of pets you have.
So there can be Categorical data, Discrete Numerical data or Continuous Numerical data.
Also, you wouldn't use mean or median for categorical data, just mode because they're not numerical values.
Types of Random Sampling
1. Random Sampling
For example drawing names out of a hat, randomly generated numbers, etc.
2. Systematic Sampling
For example, choosing every 10th person from a list of names, or testing every 100th item on a production line.
3. Stratified Sampling
This one is more complicated. Say your class has 50 students, 10 male and 40 female. You need to pick a focus group or something from your class of 5 students. Then using stratified sampling, you should pick 1 male and 4 females so the ratio of the students stays the same.
You need 5 out of 50 students = 5/50 = 1/10.
So choose 1/10 of male students = 1/10 x 10 = 1
And choose 1/10 of female students = 1/10 x 40 = 4
That gives how many of each you should pick, and then you could use random sampling or systematic sampling to pick the 1 male or 4 females from the class.
Hope this helps a little bit.