What are Population and Sample?

The entire group about whom you want to make conclusions is a population.
A sample is a subset of the population you will collect data from.
The sample size is always smaller than the population’s total size.
The population moments most often used are: 

1. mean
2. variance
3. skewness
4. kurtosis

Why are population and sample important?

For researchers to generalize results from observations of the sample to the target population, they need a simple that is typical of the target population. Both the sampling frame and the sample should, in theory, be representative of the population in every way.

When conducting research or performing statistical analyses, it is crucial to understand the concepts of population and simplicity. The population refers to the entire group or universe of interest, while a sample is a subset of that population that is selected for data collection and analysis. The sample size is always smaller than the total population size, making it more manageable and cost-effective to collect data.

Population moments such as the mean, variance, skewness, and kurtosis are frequently used to describe the characteristics of the population. These moments are used to calculate various statistics and parameters, such as the standard deviation, that help researchers understand and make predictions about the

It is important to ensure that the sample is representative of the target  to ensure that the conclusions drawn from the sample can be generalized to the . The sampling frame, which is the list or process used to select the sample, should be representative of the  in every way to obtain a valid sample.

A well-chosen sample can provide accurate and reliable information about the , allowing researchers to make informed decisions and draw accurate conclusions. Therefore, understanding the concepts of population and sample is essential for any researcher or analyst who wants to draw meaningful insights from their data.