In order to estimate some characteristic within a large group, or population, a smaller group that is a subset of the population, known as a sample, is often used. Samples can be random or biased.

• A random sample of a population is selected with the goal of finding a representation of the
  entire population without any preference.
  
  
• In a biased sample of a population the sample is chosen with some favoritism.

Let's know more about random samples and biased samples.

Types of Random Samples
Simple Random Sample	A sample that is as likely to be chosen as any other sample from the population.	Example. Each student's name is written on a piece of paper. The names are placed in a bowl, and names are picked without looking.
Stratified Random Sample	The population is divided into similar, nonoverlapping groups. Then a simple sample is chosen from each group.
Systematic Random Sample	Each item is selected according to a specific time or unit interval.

Types of Biased Samples
Convenience Sample	Any sample that consists of population items that are easily accessed.	Example. To represent all the students attending to a school, the principal surveys the students in one math class.
Voluntary Response Sample	A sample which includes only willing participants.	Example. Students at a school who wish to express their opinion are asked to complete an online survey.