Sampling Strategy: A dissertation guide. In undergraduate and master's level dissertations, the Sampling Strategy section is an important component of your Research Strategy chapter (usually Chapter Three: Research Strategy). Whilst students sometimes assume that sampling is only important when using a quantitative research design, questionnaires and/or quantitative data, this is not the case 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/findings. 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 Extreme (or deviant) case sampling. Extreme (or deviant) case sampling is a type of purposive sampling that is used to focus on cases that are special or unusual, typically in the sense that the cases highlight notable outcomes, failures or successes
Purposive 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 dissertation sampling 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 dissertation sampling about dissertation sampling population under normal circumstances. Typically, we refer to the population of a country or region dissertation sampling, such as the United States or Dissertation sampling 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, dissertation sampling.
These units could be peoplecases and pieces of data. Some examples of each of these types of population are present below:, dissertation sampling. 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. Customer transactions at Wal-Mart or Tesco between two time points e, dissertation sampling.
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 of Facebookthis would imply that we were interested in all million or more Facebook users, 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, dissertation sampling, if the population you were interested in was more specificyou should make this clear, dissertation sampling.
Perhaps our population is not Facebook usersbut frequent, male Facebook users in 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 peopledissertation sampling, cases 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 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.
For example, dissertation sampling the population dissertation sampling 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 Fortune 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.
In such cases, it is often more appropriate to dissertation sampling 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. Whilst we discuss more about sampling and why we sample later in this article, the important point to remember here is that a sample consists of only those units in this case, Facebook users from our population of interest i, dissertation sampling.
The sample size is simply the number of units in your sample. In the example above, the sample size selected may be just or of the Facebook users that are part of our population of frequent, male, Dissertation sampling users in the United States. As a result, dissertation sampling, 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 dissertation sampling which you select units. This is the case when using certain types of sampling technique i. This list can be referred to as the dissertation sampling frame.
We dissertation sampling more about sampling frames in the article: Probability dissertation sampling. Sampling bias occurs when the units that are selected from the population for inclusion dissertation sampling your sample are not characteristic of i. This can lead to your sample being unrepresentative of the population you are interested in. 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 people as they pass by how often they went to Broadway shows in a given year would dissertation sampling 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 dissertation sampling 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 dissertation sampling reflected the Broadway example aboveare prone to greater bias than probability sampling techniques.
We discuss sampling techniques further next. As we have mentioned dissertation sampling, when we are interested in a population, we typically study a sample of that population rather than attempt to study the whole population e, dissertation sampling.
If we imagine that our desired sample size was just of these Facebook users, dissertation sampling, the question arises: How do we know what Facebook users to invite to take part in our sample? In other words, dissertation sampling, what Facebook users will become part of our sample? The purpose of sampling techniques is to help you select units e. Broadly speaking, dissertation sampling, 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 select 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 samplingdissertation sampling, convenience samplingsnowball sampling and self-section sampling.
We discuss non-probability sampling in more detail in the article, Non-probability sampling. We also discuss each of these different types of non-probability sampling technique, dissertation sampling, how to carry them out, and their advantages and disadvantages [see the articles: Quota samplingdissertation sampling, Purposive 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. Population The word population is different when used in research compared with the way we think about a population under normal circumstances.
Some examples of each dissertation sampling these types of population are present below: People Students dissertation sampling at a university e. Recruitment agencies in Greater London, dissertation sampling, 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 Dissertation sampling of data Customer transactions at Dissertation sampling or Tesco between two time points e.
Units As discussed above, the population that you are interested consists of unitswhich 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. Sample Size The sample size is simply the number of units in your sample, dissertation sampling. 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 that are selected from the population for inclusion in your sample are not characteristic of i. Sampling techniques 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, dissertation sampling.
Probability sampling techniques Probability sampling techniques use random selection i, dissertation sampling. Non-probability sampling techniques Non-probability sampling techniques refer on the subjective judgement of the researcher when selecting units from the population to be included in the sample.
Dissertation sampling overview
, time: 12:07Sampling Strategy: A dissertation guide | Lærd Dissertation
Our custom papers allow you to improve your academic ratings. We offer a 24 hours certified online support. Cheap dissertation writing services online by uk experts. In The sampling strategy that you select in your dissertation should naturally flow from your chosen research design and research methods, as well as taking into account issues of research ethics. To set the sampling strategy that you will use in your dissertation, you need to follow three steps: (a) understand the key terms and basic principles; (b) determine which sampling technique you will use Where is the best dissertation help at an affordable price? March 3, Even if the deadline for completing your thesis is pretty tight, a professional dissertation writer will help you to beat it. February 28, Writers from top-rated dissertation writing services come from a wide range of countries. February 25,
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