Sampling: The Basics. Sampling is an important component of any piece of research because of the significant impact that it can have on the quality of your results/blogger.com you are new to sampling, there are a number of key terms and basic principles that act as a foundation to the subject. This article explains these key terms and basic principles Our core thesis is that because convenience samples of homogeneous populations (i.e., homogeneous convenience samples) are more likely to be representative than convenience samples of heterogeneous populations (i.e., conventional convenience samples), homogeneous convenience samples should, on average, yield more valid (less unbiased) estimates than conventional data for their dissertation projects and are typically faced with constraints that result in their samples being viewed as mere convenience samples. In describing their sampling plan and its limitations, students often struggle to evaluate the quality of their sampling procedures. This poster takes the view that all samples of human participants are
Convenience sampling | Lærd Dissertation
If you are new to sampling, there are a number of key terms and basic principles that act as a foundation to the subject. This article explains these key terms and basic principles.
Rather than a comprehensive look at sampling, the article presents the sampling basics that you would need to know if you were an undergraduate or master's level student about to perform a dissertation or similar piece of research. It also provides links to other articles within the Sampling Strategy section of this website that you may find useful. Some of the key sampling terms you will come across include populationunitssamplesample sizesampling framesampling techniques and sampling bias.
Each is discussed in turn:. The word population is different when used in research compared with the way we think about a population under normal circumstances. Typically, we refer to the population of a country or regionsuch as the United States or Great Britain. However, in research and the theory of samplingthe word population has a different meaning.
In sampling, a population signifies the units that we are interested in studying, convenience sampling dissertation.
These units could be peoplecases and pieces of data. Some examples of each of these types of population are present below:, convenience sampling dissertation. Students enrolled at a university e. Recruitment agencies in Greater London, England Law firms in Manhattan, New York, United States The World Trade Organisation WTO The European Parliament Countries that are members of NATO Signatories of the Helsinki Accord, convenience sampling dissertation.
Customer transactions at Wal-Mart or Tesco between two time points e. When thinking about the population you are interested in studying, it is important to be precise.
For example, if we say that our population is users convenience sampling dissertation Facebookthis would imply that we were interested in all million or more Facebook convenience sampling dissertation, irrespective of what country they were in, whether they were male or female, what age they were, how often they used Facebook, and so forth. However, if the population you were interested in was more specificyou should make this clear.
Perhaps our population is not Facebook usersbut frequent, male Facebook users convenience sampling dissertation the United States. When we come to describe our population further, we would also need to define what we meant by frequent users e.
As discussed above, the population that you are interested consists of unitswhich can be peoplecases or pieces of data. These terms can sometimes be used interchangeably. In this website, we use the word units whenever we are referring to those things that make up a population. However, since you may find other textbooks referring to these convenience sampling dissertation as people, cases, or pieces of data, we have provided some further clarification below:.
The population you are interested in consists of one or more units. For example, if the population we were interested in was all million or more Facebook users, each of these Facebook users would be a unit. So we would have million or more units in our population.
If we were interested in CEOs or Presidents of Convenience sampling dissertation companies, the CEOs or Presidents would be our units. Sometimes the word units is replaced with the word cases. As highlighted in the population examples above, sometimes the populations we are interested in are organisations, institutions and countries, convenience sampling dissertation. In such cases, it is often more appropriate to refer to each of these e.
You may be interested in a population that consists of only one case e. Finally, researchers sometimes refer to populations consisting of data or pieces of data instead of units or cases. For example, researchers may be interested in customer transactions at a particular supermarket e. When we are interested in a population, it is often impractical and sometimes undesirable to try and study the entire population.
For example, if the population we were interested in was frequent, male Facebook users in the United Statesthis could be millions of users i. If we chose to study these Facebook users using structured interviews i. Therefore, we choose to study just a sample of these Facebook users, convenience sampling dissertation. Whilst we discuss more about sampling and why we sample later in this article, the important point to convenience sampling dissertation here is that a sample consists of only those units in this case, Facebook users from our population of interest i.
The sample size is simply the number of units in your sample, convenience sampling dissertation. In the example above, the sample size selected may be just or convenience sampling dissertation the Facebook users that are part of our population of frequent, male, Facebook users in the United States.
As a result, sample size calculations are sometimes performed to determine how large your sample size needs to be to avoid such problems. However, these calculations can be complex, and are typically not performed at the undergraduate and master's level when completing a dissertation.
The sampling frame is very similar to the population you are studying, and may be exactly the same. When selecting units from the population to be included in your sample, it is sometimes desirable to get hold of a list of the population from which you select units.
This is the case when using certain types of sampling technique i. This list can be referred to as the sampling frame. We explain more about sampling frames in the article: Probability sampling.
Sampling bias occurs when the units that are selected from the population for inclusion in your sample are not characteristic of i. This can lead to your sample being unrepresentative of the population you are interested in, convenience sampling dissertation. For example, you want to measure how often residents in New York go to a Broadway show in a given year. Clearly, standing along Broadway and asking convenience sampling dissertation as they pass by how often they went to Broadway shows in a given year would not make sense because a higher proportion of those passing by are likely to have just come out of a show.
The sample would therefore be biased. For this reason, we have to think carefully about the types of sampling techniques we use when selecting units to be included in our sample. Some sampling techniques, such as convenience samplinga type of non-probability sampling which reflected the Broadway example aboveconvenience sampling dissertation, are prone to greater bias than probability sampling techniques. We discuss sampling techniques further next. As we have mentioned above, when we are interested in a population, we typically study a sample of that population rather than attempt to study the whole population e.
If we imagine that our desired sample size was just of these Facebook users, the question arises: How do we know what Facebook users to invite to take part in our sample? In other words, what Facebook users will become part of our sample?
The purpose of sampling techniques is to help you select units e. Broadly speaking, there are two groups of sampling technique: probability sampling techniques and non-probability sampling techniques. Probability sampling techniques use random selection i. These procedures i. Since the characteristics of the sample researchers are interested in vary, different types of probability sampling technique exist to help you convenience sampling dissertation the appropriate units to be included in your sample.
These types of probability sampling technique include simple random samplingsystematic random samplingstratified random sampling and cluster sampling. We discuss probability sampling in more detail the article, Probability sampling.
We also discuss each of these different types of probability sampling technique, how to carry them out, and their advantages and disadvantages [see the articles: Simple random samplingSystematic random sampling and Stratified random sampling ]. Non-probability sampling techniques refer on the subjective judgement of the researcher when selecting units from the population to be included in the sample.
For some of the different types of non-probability sampling technique, the procedures for selecting units to be included in the sample are very clearly defined, just like probability sampling techniques. However, in others e. Overall, the types of non-probability sampling technique you are likely to come across include quota samplingpurposive samplingconvenience samplingsnowball sampling and self-section sampling.
We discuss non-probability sampling in more detail convenience sampling dissertation the article, Non-probability sampling. We also discuss each of these different types of non-probability sampling technique, how convenience sampling dissertation carry them out, and their advantages and disadvantages [see the articles: Quota samplingPurposive samplingConvenience samplingSnowball sampling and Self-selection sampling ].
If you want to know more about the sampling techniques you may use in your dissertation, read up on probability sampling and non-probability sampling. Population Units Sample Sample size Sampling frame Sampling bias Sampling techniques, convenience sampling dissertation. Population The word population is different when used in research compared with the convenience sampling dissertation we think about a population under normal circumstances, convenience sampling dissertation.
Some examples of each of these types of population are present below: People Students enrolled at a university e. Recruitment agencies in Greater London, England Law firms in Manhattan, convenience sampling dissertation, New York, United States The World Trade Organisation WTO The European Parliament Countries that are members of NATO Signatories of the Helsinki Accord Pieces of data Customer transactions at Wal-Mart or Tesco between two time points e.
Units As discussed above, the population that you are interested consists of unitsconvenience sampling dissertation, which can be peoplecases or pieces of data. However, since you may find other textbooks referring to these units as people, cases, or pieces of data, we have provided some further clarification below: The population you are interested in consists of one or more units.
Sample When we are interested in a population, it is often impractical and sometimes undesirable to try and study the entire population, convenience sampling dissertation. Sample Size The sample size is simply the number of units in your sample. Sampling frame The sampling frame is very similar to the population you are studying, and may be exactly the same.
Sampling bias Sampling bias occurs when the units convenience sampling dissertation are selected from the population for inclusion in your sample are not characteristic of i, convenience sampling dissertation. Sampling techniques As we have mentioned above, when we are interested in a population, convenience sampling dissertation, we typically study a sample of that population rather convenience sampling dissertation attempt to study the whole population e.
Probability sampling techniques Probability sampling techniques use random selection i. Non-probability sampling techniques Non-probability sampling techniques refer on the subjective judgement of the researcher when convenience sampling dissertation units from the population to be included in the sample.
Convenience Sampling
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Our essay writers are standing by to Dissertations With Convenience Sampling take the work off of your hands. Every essay writer is highly qualified and fully capable of completing the paper on time. On-demand options. Call the Shots. Chat with the writer and have changes made as you go/10() doctoral thesis and also “convenience sampling” was frequently preferred as sampling method and sample size was generally about “ people” because researchers preferred survey model. Keywords: environmental education, content analysis, master‟s thesis, doctoral dissertations data for their dissertation projects and are typically faced with constraints that result in their samples being viewed as mere convenience samples. In describing their sampling plan and its limitations, students often struggle to evaluate the quality of their sampling procedures. This poster takes the view that all samples of human participants are
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