Sampling is a process of selecting a portion of population to represent the enti

Step 1
Sampling: Sampling is a technique of selecting individual members or a subset of the population from the entire population to make statistical inferences from them and estimate characteristics of the whole population. Different sampling methods are widely used by researchers in different fields. It is also a time-convenient and a cost-effective method and hence forms the basis of any research designs.
There are two types of sampling techniques which are further divided into several types of sampling methods.
1) Probability sampling: In this type of technique all the members have an equal opportunity to be a part of the sample with this selection parameter.
2) Non-probability sampling: In this sampling technique it is difficult for all elements of a population to have equal opportunities to be included in a sample.
Step 2
Types of probability sampling:
1. Simple random sampling.
2. Cluster sampling
3. Stratified sampling
4. Systematic sampling
Types of non-probability sampling:
1. Convenience sampling
2. Purposive sampling
3. Snowball sampling
Step 3
1. Simple random sampling:
One of the best and easiest probability sampling techniques that helps in saving time and resources, is the Simple Random Sampling method. It is a reliable method of obtaining information where every single member of a population is chosen randomly, merely by chance. Each individual has the same probability of being chosen to be a part of a sample. For example, in an organization of 600 employees, if the HR team decides on conducting team building activities, it is highly likely that they would prefer picking chits out of a bowl. In this case, each of the 600 employees has an equal opportunity of being selected.
2. Cluster sampling:
This is a method in which the researchers divide the entire population into sections or clusters that represent the population. Clusters are identified and included in a sample based on demographic parameters like age, sex, location, etc. This makes it very simple for a survey creator to derive effective inference from the feedback. For example, if the United States government wishes to evaluate the number of immigrants living in the Mainland US, they can divide it into clusters based on states such as California, Texas, Florida, Massachusetts, Colorado, Hawaii, etc. This way of conducting a survey will be more effective as the results will be organized into states and provide insightful immigration data.
Step 4
3. Stratified sampling:
This is a sampling technique in which the researcher divides the population into smaller groups that don’t overlap but represent the entire population. While sampling, these groups can be organized and then draw a sample from each group separately. For example, a researcher looking to analyze the characteristics of people belonging to different annual income divisions will create strata (groups) according to the annual family income. Eg – less than $20,000, $21,000 – $30,000, $31,000 to $40,000, $41,000 to $50,000, etc. By doing this, the researcher concludes the characteristics of people belonging to different income groups. Marketers can analyze which income groups to target and which ones to eliminate to create a roadmap that would bear fruitful results.
4. Systematic Sampling:
Researchers use this technique to choose the sample members of a population at regular intervals. It requires the selection of a starting point for the sample and sample size that can be repeated at regular intervals. This type of sampling method has a predefined range, and hence this sampling technique is the least time-consuming. For example, a researcher intends to collect a systematic sample of 500 people in a population of 5000. He/she numbers each element of the population from 1-5000 and will choose every 10th individual to be a part of the sample (Total population/ Sample Size ${\displaystyle =\frac{5000}{500}=10}$).