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. If not, the results of the study could be misleading or skewed. To unlock this lesson you must be a Study. Did you know… We have over college courses that prepare you to earn credit by exam that is accepted by over 1, colleges and universities.
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The videos on Study. Students in online learning conditions performed better than those receiving face-to-face instruction. 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.
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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. The five steps to sampling are: Identify the population Specify a sampling frame Specify a sampling method Determine the sample size Implement the plan It is important for researchers to follow these steps so that their sample adequately represents their population.
Learning Outcomes Following this lesson, you should have the ability to: In most cases, the target population, such as students in JS1, is simply too large for the researcher to plan a quality research study. Collecting millions of questionnaires from every JS1 student would present the following challenges: Millions of naira would be spent just to print the questionnaires, let alone transportation costs to distribute the questionnaires to all JS1 students.
Researchers would have difficulties finding all JS1 students, particularly in village areas. Unqualified research assistants would have to be enlisted to assist in data collection, reducing the quality of data received. Years would be spent distributing and collecting the questionnaires, let alone coding the questionnaire responses. Since it will take so long to collect data from the entire population, the data from the first group of students sampled will likely be outdated by the time the last group of students is sampled.
Does this therefore mean that the target population has to be restricted to such a small group - such as all JS1 students in Baptist Academy - so that the researcher can access the entire population? Research methodologists have developed sampling procedures that should identify a sample that is representative of the population, meaning that the sample closely resembles the target population on all relevant characteristics.
The theory of sampling is as follows: Researchers want to gather information about a whole group of people the population. Researchers can only observe a part of the population the sample. The findings from the sample are generalized, or extended, back to the population.
Therefore, the key question in sampling is How representative is the sample of the target population? This question is the foundation of population validity, the degree to which the results of a study can be generalized from the sample to the target population. The analogy of a fruit market can be used when thinking about the population, the sample, and the sampling technique. The first step in sampling is to identify the unit of analysis. This was described in Chapter 11, Identify the Population.
Let's say that you are conducting research related to a fruit market. What will be studied in the fruit market? Is it a type of fruit or the fruit sellers themselves? Let's say you identify citrus fruit as the unit of analysis, and your population is all citrus fruit within the Bauchi Road fruit market. There are too many pieces of citrus fruit for you to study in that market, so you must select only a sample of the citrus fruit. A common error in sampling is that the sample and population are not identical.
For example, the sample may be too narrow. If the population is all citrus fruit within the Bauchi Road fruit market, then the sample cannot only consist of lemons because your sample would be missing oranges, grapefruit, and limes.
Therefore, you must find a way of selecting a representative sample of citrus fruit from your population. To apply to an educational study, perhaps one may say that the population is all university students, but only university students in public schools are sampled. Another common error is to make the population too broad. Some may say that the population is all mangoes in the Bauchi Road fruit market, but they are really only interested in green mangoes. If only green mangoes are of interest, then the population should be green mangoes in the Bauchi Road fruit market.
In educational research, sometimes researchers are only interested in a population with a certain characteristic, such as student who has not chosen a career in the case of career counseling. Thus, the population and sample must be the same. Before selecting a sampling procedure, first consider the following: Select the unit of analysis.
When selecting the sample, it is imperative that the sampling technique selects cases based on this unit of analysis. In other words, if the unit of analysis is students, then the sampling technique must focus solely on how the students were selected.
It would be an error to describe the selection of schools as the sampling technique when the unit of analysis is students. Determine how many units need to be sampled. This step is a tricky balancing act. On the one hand, larger samples tend to be more representative of the target population and provide stronger statistical power.
On the other hand, larger samples can decrease the quality of the research study, particularly for experimental and quasi-experimental designs. In experimental designs, if many people participate in the treatment, then the quality of treatment that each individual receives might suffer, resulting in inaccurate conclusions.
It is a truism that overpopulation in classrooms reduces the impact of instruction; if there are too many students in the class, then the teaching will not be as effective. Likewise, we should equally avoid the problem of overpopulation in experiments: Therefore, smaller treatment groups are generally preferable. In general, descriptive designs require at least participants, correlational designs require at least 30 participants, and experimental, quasi-experimental, and causal-comparative designs require at least 15 participants per group.
The size of the sample in experiments depend on how effective the treatment is. If you have a very effective treatment, then only a few participants are necessary.
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.
Sampling is the process whereby a researcher chooses his or her sample. The five steps to sampling are: The five steps to sampling are: Identify the population.
Research methodologists have developed sampling procedures that should identify a sample that is representative of the population, meaning that the sample closely resembles the target population on all relevant characteristics. In fact, the sampling procedure largely depends on who are your respondents. If it is the general public you may go for random sampling if the the area you are covering is not that large otherwise.
It consist sample definition, purpose of sampling, stages in the selection of a sample, types of sampling in quantitative researches, types of sampling in qualitative researches, and ethical Considerations in . 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.