A visual representation of the sampling process. In statistics, quality assurance, and survey methodology, sampling is the selection of a subset or a statistical sample (termed sample for short) of individuals from within a statistical population to estimate characteristics of the whole population. Statisticians attempt to collect samples that are representative of the population. By Ashley Crossman Updated on January 29, 2020 Simple random sampling is the most basic and common type of sampling method used in quantitative social science research and in scientific research generally . The main benefit of the simple random sample is that each member of the population has an equal chance of being chosen for the study. Random sampling is also used for other sampling techniques such as stratified sampling. Stratified sampling requires another sampling method such as a simple random sample to generate a random selection of data values once the data is divided into subgroups (or subsets).This means that each item of data has an equal probability of being chosen and each subgroup within the sample is represented The numbers below that are in bold print correspond to this: 23 44 92 72 75 19 82 88 29 39 81 82 88. At this point, there are a few things to note about this particular example of the process of selecting a simple random sample. The number 92 was omitted because this number is greater than the total number of students in our population. Simple random sampling: Definition, examples, and how to do it How can you pick a sample that's truly random and representative of the participant population? Simple random sampling is the sampling method that makes this easy. Learn how it works in our ultimate guide. A systematic sample that is also random is referred to as a systematic random sample. This type of random sample can sometimes be substituted for a simple random sample. When we make this substitution we must be certain that the method we use for our sample does not introduce any bias. Learn more about how the sampling technique known as Systematic sampling A researcher divides a study population into relevant subgroups then draws a sample from each subgroup. techniques are somewhat less tedious but offer the benefits of a random sample. As with simple random samples, you must be able to produce a list of every one of your population elements. Random Sampling Example Example 1: A company has 500 products, and they want to randomly select 20 of them for quality testing. What is the probability of any single product getting selected? Solution: The chance of one-time selection is: P = n/N ⇒ P = 20/500 ⇒ P = 4% Simple Random Sampling Definition. Simple random sampling is the method of randomly selecting samples from a population based on the type and nature of the study. Researchers use this technique of studying a social group to find out the possibility of an outcome. Stratified Sampling Examples. Ensuring students from all grades are represented in a school study: Let's say you need a sample of 100 from 1000 students who were asked about their preferred subject.To avoid selection bias due to different grades having different subjects, the students can be grouped according to the grade, and students are chosen from each grade. zbgFkb.