There are numerous ways of getting a sample, but here are the most commonly used sampling methods:. The purest form of sampling under the probability approach, random sampling provides equal chances of being picked for each member of the target population. Examples of stratum include mothers, fathers, students, teachers, females, males, etc. Sampling error is usually lower in stratified sampling than in random sampling. In systematic sampling , every Nth name is selected from the list of the members of the target population.
For instance, the sample will include the participants listed in every 10th from the list. That means the 10th, 20th, 30th and so on will be selected to become the members of the sample group. This non-probability sampling method is used when there are only a few available members of the target population who can become the participants in the survey.
Another non-probability method, quota sampling also identifies strata like stratified sampling, but it also uses a convenience sampling approach as the researcher will be the one to choose the necessary number of participants per stratum. As the name suggests, purposive sampling means the researcher selects participants according to the criteria he has set.
This is only used when you are confident enough about the representativeness of the participant regarding the whole target population. Aside from the estimated number of people in the target population, the sample size can be influenced by other factors such as budget, time available, and the target degree of precision. The sample size can be calculated using the formula:. Strictly adhering to the sample size facilitates a higher precision in the results because having participants less than the sample size leads to low representativeness of the target population.
On the other hand, going over the sample size may cause a diminished rate of enhancement in the precision of the survey outcomes. Check out our quiz-page with tests about:.
Sarah Mae Sincero May 10, Methods of Survey Sampling. Retrieved Sep 11, from Explorable. The text in this article is licensed under the Creative Commons-License Attribution 4.
You can use it freely with some kind of link , and we're also okay with people reprinting in publications like books, blogs, newsletters, course-material, papers, wikipedia and presentations with clear attribution. Because sampling isn't as straightforward as it initially seems, there is a set process to help researchers choose a good sample. Let's look closer at the process and importance of sampling. So Brooke wants to choose a group of college students to take part in her study. To select her sample, she goes through the basic steps of sampling.
Identify the population of interest. A population is the group of people that you want to make assumptions about. For example, Brooke wants to know how much stress college students experience during finals.
Her population is every college student in the world because that's who she's interested in. Of course, there's no way that Brooke can feasibly study every college student in the world, so she moves on to the next step. Specify a sampling frame. A sampling frame is the group of people from which you will draw your sample. For example, Brooke might decide that her sampling frame is every student at the university where she works.
Notice that a sampling frame is not as large as the population, but it's still a pretty big group of people. Brooke still won't be able to study every single student at her university, but that's a good place from which to draw her sample. Specify a sampling method. There are basically two ways to choose a sample from a sampling frame: There are benefits to both.
Basically, if your sampling frame is approximately the same demographic makeup as your population, you probably want to randomly select your sample, perhaps by flipping a coin or drawing names out of a hat. But what if your sampling frame does not really represent your population? For example, what if the school where Brooke works has a lot more men than women and a lot more whites than minority races?
In the population of every college student in the world, there might be more of a balance, but Brooke's sampling frame her school doesn't really represent that well. In that case, she might want to non-randomly select her sample in order to get a demographic makeup that is closer to that of her population.
Determine the sample size. In general, larger samples are better, but they also require more time and effort to manage. If Brooke ends up having to go through 1, surveys, it will take her more time than if she only has to go through 10 surveys. But the results of her study will be stronger with 1, surveys, so she like all researchers has to make choices and find a balance between what will give her good data and what is practical.
Once you know your population, sampling frame, sampling method, and sample size, you can use all that information to choose your sample. As you can see, choosing a sample is a complicated process. You might be wondering why it has to be that complicated. Why bother going through all those steps? Why not just go to a class and pull some students out and have them fill out the survey? Why is sampling so important to research? Get access risk-free for 30 days, just create an account.
To answer those questions, let's look at an example of an actual study that was done in the mids. A researcher mailed out surveys to a bunch of married women and asked them questions about their marriage.
As you can imagine, this study sent shockwaves through America as husbands looked at their wives and calculated the probability of dissatisfaction or affairs. Those who got the survey, filled it out, and returned it were much more likely to be dissatisfied than those who didn't return it. Maybe those who were happy in their marriage were too busy having fun with their spouse to cheat.
That's why sampling is so important to research. If a sample isn't chosen carefully and systematically, it might not represent the population. And if it doesn't represent the population, then the study can't be generalized to the world beyond the study. Let's go back to Brooke for a moment. She wants to know, in general, how much stress college students experience during finals.
Let's say that she decides to save some time and bypass the normal sampling method. Instead, she just sets up a table outside the mental health office on campus where students go to see counselors. As students go in or out of the office, she gives them the survey.
But in this example, Brooke's sample might end up being only college students who are seeing counselors. They might be more anxious or depressed or high-strung in general, so the stress of finals might hit them particularly hard. As a result, Brooke's sample doesn't represent the population, and she might end up thinking that college students experience more stress than they actually do. The sample of a study is the group of subjects in the study.
Sampling is the process whereby a researcher chooses his or her sample. The five steps to sampling are:. It is important for researchers to follow these steps so that their sample adequately represents their population.
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By creating an account, you agree to Study. Explore over 4, video courses. Find a degree that fits your goals. What is Sampling in Research? In this lesson, we'll look at the procedure for drawing a sample and why it is so important to draw a sample that represents the population. Try it risk-free for 30 days. An error occurred trying to load this video.
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Register to view this lesson Are you a student or a teacher? I am a student I am a teacher. What teachers are saying about Study. Are you still watching? Your next lesson will play in 10 seconds. Add to Add to Add to. Want to watch this again later? Sampling Techniques In Scientific Investigations. Selecting a Problem to Research. What is a Hypothesis? What is a Research Proposal? Multistage, Multiphase, and Cluster Samples. What is Hypothesis Testing? What Is Social Science Research?
The Importance of Understanding Research Methodology. The Importance of Measurement in the Research Process. Research Methods in Psychology: Research Methods in Psychology for Teachers: Information Systems and Computer Applications. The sample of a study can have a profound impact on the outcome of a study. Sampling Brooke is a psychologist who is interested in studying how much stress college students face during finals. Process So Brooke wants to choose a group of college students to take part in her study.
Importance As you can see, choosing a sample is a complicated process. Try it risk-free No obligation, cancel anytime. Want to learn more? Select a subject to preview related courses: Lesson Summary The sample of a study is the group of subjects in the study.
Sampling Methods. Sampling and types of sampling methods commonly used in quantitative research are discussed in the following module. Learning Objectives: Define sampling and randomization. Explain probability and non-probability sampling and describes the different types of each.
There are many methods of sampling when doing research. This guide can help you choose which method to use. Simple random sampling is the ideal, but researchers seldom have the luxury of time or money to access the whole population, so many compromises often have to be made.
This was a presentation that was carried out in our research method class by our group. RESEARCH METHOD - SAMPLING Define the target population Select a sampling frame Conduct fieldwork Determine if a probability or nonprobability sampling method will be chosen Plan procedure for selecting sampling units Determine sample size . In probability sampling it is possible to both determine which sampling units belong to which sample and the probability that each sample will be selected. The following sampling methods are examples of probability sampling: Of the five methods listed above, students have the most trouble.
Video: What is Sampling in Research? - Definition, Methods & Importance - Definition, Methods & Importance The sample of a study can have a profound impact on the outcome of a study. Then, because some types of sampling rely upon quantitative models, we'll talk about some of the statistical terms used in sampling. Finally, we'll discuss the major distinction between probability and Nonprobability sampling methods .