What is the Difference Between Sample and Population?

The main difference between a sample and a population is that a population refers to the entire group of individuals, objects, or events being studied, while a sample is a subset of the population that is used for analysis. Here are some key differences between the two:

Size: The size of the sample is always less than the total size of the population.
Representation: A sample represents the characteristics of the population, while the population includes all members of the defined group.
Data Collection: In research, collecting data from the entire population is often difficult or impossible, especially for larger and more dispersed populations. Samples are used to make more precise inferences about the population.
Statistical Analysis: Descriptive statistics can be used to analyze both populations and samples. For example, measures of central tendency, such as mean and median, and measures of variability, such as standard deviation and range, can be calculated for both populations and samples.

In summary, a population is the entire group that you want to draw conclusions about, while a sample is the specific group from which you will collect data. Samples are used to make generalizations and draw conclusions about the larger population, and proper sampling techniques ensure that research findings are reliable and representative of the larger population.