What are the main types of sample selection?
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If you're behind a web filter, please make sure that the domains *.kastatic.org and *.kasandbox.org are unblocked. We know that statistical research helps in drawing several conclusions based on the requirement of the experts. This uses the data collected for a specific purpose. We can collect the data using various sampling methods in statistics. However, the type of sampling method is chosen based on the objective of the statistical research. The statistical research is of two forms:
In this article, let us discuss the different sampling methods in research such as probability sampling and non-probability sampling methods and various methods involved in those two approaches in detail. Table of Contents:
What are the sampling methods or Sampling Techniques?In Statistics, the sampling method or sampling technique is the process of studying the population by gathering information and analyzing that data. It is the basis of the data where the sample space is enormous. There are several different sampling techniques available, and they can be subdivided into two groups. All these methods of sampling may involve specifically targeting hard or approach to reach groups.
Types of Sampling MethodIn Statistics, there are different sampling techniques available to get relevant results from the population. The two different types of sampling methods are::
 Also, read: Sample statistic What is Probability Sampling?The probability sampling method utilizes some form of random selection. In this method, all the eligible individuals have a chance of selecting the sample from the whole sample space. This method is more time consuming and expensive than the non-probability sampling method. The benefit of using probability sampling is that it guarantees the sample that should be the representative of the population. Probability Sampling TypesProbability Sampling methods are further classified into different types, such as simple random sampling, systematic sampling, stratified sampling, and clustered sampling. Let us discuss the different types of probability sampling methods along with illustrative examples here in detail. Simple Random SamplingIn simple random sampling technique, every item in the population has an equal and likely chance of being selected in the sample. Since the item selection entirely depends on the chance, this method is known as “Method of chance Selection”. As the sample size is large, and the item is chosen randomly, it is known as “Representative Sampling”. Example: Suppose we want to select a simple random sample of 200 students from a school. Here, we can assign a number to every student in the school database from 1 to 500 and use a random number generator to select a sample of 200 numbers. Systematic SamplingIn the systematic sampling method, the items are selected from the target population by selecting the random selection point and selecting the other methods after a fixed sample interval. It is calculated by dividing the total population size by the desired population size. Example: Suppose the names of 300 students of a school are sorted in the reverse alphabetical order. To select a sample in a systematic sampling method, we have to choose some 15 students by randomly selecting a starting number, say 5. From number 5 onwards, will select every 15th person from the sorted list. Finally, we can end up with a sample of some students. Stratified SamplingIn a stratified sampling method, the total population is divided into smaller groups to complete the sampling process. The small group is formed based on a few characteristics in the population. After separating the population into a smaller group, the statisticians randomly select the sample. For example, there are three bags (A, B and C), each with different balls. Bag A has 50 balls, bag B has 100 balls, and bag C has 200 balls. We have to choose a sample of balls from each bag proportionally. Suppose 5 balls from bag A, 10 balls from bag B and 20 balls from bag C. Clustered SamplingIn the clustered sampling method, the cluster or group of people are formed from the population set. The group has similar significatory characteristics. Also, they have an equal chance of being a part of the sample. This method uses simple random sampling for the cluster of population. Example: An educational institution has ten branches across the country with almost the number of students. If we want to collect some data regarding facilities and other things, we can’t travel to every unit to collect the required data. Hence, we can use random sampling to select three or four branches as clusters. All these four methods can be understood in a better manner with the help of the figure given below. The figure contains various examples of how samples will be taken from the population using different techniques. What is Non-Probability Sampling?The non-probability sampling method is a technique in which the researcher selects the sample based on subjective judgment rather than the random selection. In this method, not all the members of the population have a chance to participate in the study. Non-Probability Sampling TypesNon-probability Sampling methods are further classified into different types, such as convenience sampling, consecutive sampling, quota sampling, judgmental sampling, snowball sampling. Here, let us discuss all these types of non-probability sampling in detail. Convenience SamplingIn a convenience sampling method, the samples are selected from the population directly because they are conveniently available for the researcher. As a result, the samples are easy to set, and the researcher did not choose the sample that outlines the entire population. What are the 5 types of samples?There are five types of sampling: Random, Systematic, Convenience, Cluster, and Stratified.
What are the 4 sampling strategies?Four main methods include: 1) simple random, 2) stratified random, 3) cluster, and 4) systematic. Non-probability sampling – the elements that make up the sample, are selected by nonrandom methods. This type of sampling is less likely than probability sampling to produce representative samples.
What is sample selection?Sampling allows the estimation of the characteristics of a population by directly observing a portion of the entire population. Researchers are not interested in the sample itself, but in what can be learned from the sample about the entire population.
What are the 4 types of random sampling?There are four primary, random (probability) sampling methods – simple random sampling, systematic sampling, stratified sampling, and cluster sampling.
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