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Concepts, relationships, and types of samples are presented. Cases to practice sampling are included. Sample size is also discussed.
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How to Choose a Sample for Your Thesis
or Dissertation
Concepts to Know
Research Popula.on The whole set of units (people, groups, events, se4ngs, etc.) on which the research is focused and the findings are expected to be generalized.
Sample Representa?ve subset of the popula?on the researcher studies when the whole popula?on is not available
Sampling Scheme Specific strategies to select samples
Sampling Design Umbrella term that includes both selec?ng strategies and sample size
Relationships to Remember
Research Problem
• What needs to be studied under a specific situa?on
Research Ques?on
• What to answer or test
Methodology • How to gather and analyze valid data
Valid Informa.on to Answer or Test Research Ques.on
Data Analysis Methods
Sampling Design
Research Design
The next slides will present a basic summary of some of the sampling schemes that are widely used in research. However, it is necessary to say that the applica?on of probabilis?c (random) schemes to quan?ta?ve research and non-‐probabilis?c (non-‐random) ones to qualita?ve studies does not imply that these are the only approaches.
In fact, Onwuegbuzie & Collins (2007) state that some form of non-‐random scheme is the most common choice used in both quan?ta?ve and qualita?ve studies and that random ones for quan?ta?ve research and non-‐random for qualita?ve studies is the second most common combina?on. Our own research into disserta?on and thesis work interna?onally demonstrates that the majority employ purposeful convenience samples. Such predominance of non-‐random samples is related to the fact that most studies in social sciences cannot be done under experimental condi?ons in which pure random selec?on is expected. Onwuegbuzie, A. & Collins, K. (2007). A typology of mixed methods sampling designs in social science research. The Qualita+ve Report, 12 (2), 281-‐316
Quantitative Research
Simple random The whole popula?on is available and any unit has the same chance of being chosen
Stra.fied random The whole popula?on is divided into subpopula?ons (strata) with respect to one or more characteris?cs that interest and units are selected from each stratum at random. Alloca?on of units can be done equal or propor?onal to the popula?on
Systema.c Popula?on is ordered according to a criterion and units are chosen from the list by selec?ng every nth one
Cluster Popula?on consists of limited groups (clusters) and sampling is focused on selec?ng clusters instead of individual units. Not all clusters are included in the sample
Mul.stage random Very large popula?ons are divided into clusters and then sub-‐clusters and units are selected at random following a general to specific direc?on
Qualitative Research (I)
Convenience Sample consists of units that are available and/ or willing to par?cipate
Purposeful Researcher is interested in studying specific groups. Selec?on of units can be done at random, stra?fied, or using more than one scheme (mixed)
Quota Units are selected in rela?on to pre-‐defined characteris?cs either in propor?on to popula?on sub-‐groups or minimum number from each sub-‐group
Snowball Similar units are required and access to them is done by asking par?cipants to recommend peers
Mul.stage purposeful Units are selected in more than one stage and always applying a purposive scheme
Qualitative Research (II)
Typical case Units are chosen because they represent the average element of what is studied
Maximum varia.on When differences are the research target, dissimilar units are chosen to form sample
Criterion Units are selected because each one of them represents one or more desired criteria
Theore.cal Units are chosen because they can provide input informa?on to build or test a theory
Mixed Methods Research
All previous schemes When choosing samples for mixed methods studies, researchers need to take into account the purpose of the study, the research ques?ons, and the stages in which the study will be developed. All those elements help them select the most appropriate sampling scheme for each stage. When generaliza?on is the main concern of a stage, the first five schemes presented are the best op?ons. When understanding is the focus of a stage, then the rest of schemes should be considered.
Cases to Practice Sampling
Quantitative Research
Options for Sampling:
1. Simple random 2. Stratified random 3. Cluster
And the answer is…….
• The research director of an educational city system that includes forty-five elementary schools wants to answer the following research question: What’s the achievement in mathematics of fifth-grade students of the school system, measured by a standardized achievement test?
It’s too expensive to administer the test to the whole popula?on and the same happens if the simple random sampling is chosen. Stra?fied random sampling implies administering the test to some of the students of a class and not to others and that may be inconvenient from the students’ point of view. Since students are organized in classes –which are in fact clusters, the most appropriate op?on is cluster sampling and that will allow to test all students in the chosen classes.
Cluster Sampling
Qualitative Research
Options for Sampling:
1. Purposeful 2. Snowball 3. Maximum variation
And the answer is…….
• A researcher wants to know the reasons why some employees of large companies have strong pro-mentoring duties views.
Since par?cipants with similar views within organiza?ons are required and they could be difficult to locate, it is appropriate to ask them to recommend poten?al subjects.
Snowball
Sample Size
Criteria to Select Sample Size (I)
• Costs (money, ?me, and effort) to get sample data. • For quan?ta?ve studies: – Popula?on size (the larger the popula?on, the larger the sample)
– Confidence interval (how much error will be allowed) – Confidence level (how much confident you want to be that your results are within the selected confidence interval)
– Standard devia?on (how much dispersion from the mean you expect)
These criteria is used by calculators to determine the most appropriate sample size for your study
Criteria to Select Sample Size (II)
• For qualita?ve studies: Samples are usually small, but the precise number is very unlikely to be determined at the beginning of the study . The main criterion is to have a sample as big as needed to have all the informa?on that might be important. Therefore, when informa?on becomes redundant, the sample size has been reached.
Criteria to Select Sample Size (III)
• For mixed studies: – Usually the sizes of the sample for each stage are different
– The mixed methods variant used influences the sample sizes. For example, in an explanatory design the same par?cipants must be included in all the stages while in an exploratory design more par?cipants are needed in the quan?ta?ve stage.
Now You Know
1. The relationship between research problem, research question, and sampling.
2. Some of the basic sampling schemes you may use to select participants for your study
Any question?
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