Population,sample and random sampling

Definition：①The totality of a class of things with some common and observable characteristics. ②In psychological research, it refers to the set of all individuals that are the focus of a particular study.

Basic unit：Individual.

Example：If you want to count the heights of Beijing college students，the population is Beijing college students.

Definition: The collection of individuals selected from the population as the research targets.

Characteristic: The subset of population.

Cause: Due to the limitation of human and financial resources, it is difficult to make statistics reach every individual. We have to select some individuals from the population as the object of study.

Sampling bias: The larger the sample is, the closer it is to the population and the more representative it is of the population. Small sample may result in sampling bias and poor representation of the population.

Advantages of sampling: ①Saving time and expenses. ②Properly sampled samples are highly representative.

Examples: If you want to count the heights of college students in Beijing, a portion of individuals from each college can be taken as a sample by random sampling.

Definition: Each element of the population has an equal chance of been selected when drawing a sample from a population.

The sample obtained by random sampling method is called random sample.

Methods: Stratified sampling (by age, sex ratio), etc.