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What are the steps for selecting a representative sample in experimental research?

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Experimental research is a method of testing hypotheses and establishing causal relationships between variables by manipulating one or more factors and observing the effects on the outcomes. To ensure the validity and generalizability of experimental results, it is essential to select a representative sample of the population of interest. A representative sample is a subset of the population that reflects its characteristics, such as demographics, attitudes, behaviors, or responses, as accurately as possible. Here are the steps for selecting a representative sample in experimental research:

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Snehil .

Advancing Immunization Through Expertise in Equity & Vaccine Cold Chain Management #Malawi #Africa #Kenya

1 Define the population

The first step is to define the population that you want to study and draw conclusions about. The population is the entire group of individuals or units that share one or more common characteristics or features relevant to your research question. For example, if you want to test the effect of a new drug on blood pressure, your population might be all adults with hypertension in a certain region or country. You should specify the criteria for inclusion and exclusion in your population, such as age, gender, health status, location, or any other relevant factors.

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Snehil .

Advancing Immunization Through Expertise in Equity & Vaccine Cold Chain Management #Malawi #Africa #Kenya
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start by defining your target group, like 'adults over 30' or 'urban high school students.' Then choose a sampling method, like random where everyone has an equal chance, or stratified where you divide your target group into subgroups and sample from each. Make sure your sample size is big enough to be reliable but manageable. Double-check that your sample reflects the diversity of your target group in terms of age, gender, location, etc. This way, your sample can accurately represent the larger group you're studying.

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Alejandro Bermejo

Doctor. Emergency Physician. Biochemistry Specialist. Professor-Researcher in Biochemistry and Theoretical Biophysics. MSc.
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In approaching research, I find that establishing a clear target population is fundamental. Defining this group, united by relevant characteristics, ensures the study's applicability. Take, for instance, exploring a new drug's impact on blood pressure in hypertensive adults within a specific region – a focused approach. The criteria, whether age, gender, or health status, serve as filters for precision. In my opinion, this meticulous definition not only sharpens the study's focus but also sets the stage for meaningful and applicable research outcomes.

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2 Choose a sampling frame

The next step is to choose a sampling frame, which is a list or source of information that identifies and provides access to the members of your population. The sampling frame should be as close as possible to the population, but it may not include all of its members or may include some that are not part of it. For example, if you use a hospital registry as your sampling frame for your drug study, you may miss some patients who are not registered or include some who do not have hypertension. You should evaluate the quality and availability of your sampling frame and try to minimize any discrepancies with your population.

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?? ?? Milica Nikolic

????Technical Support Agent and, aspiring Veterinary Clinical Pathologist
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This sampling frame is actually a database from which you pull population sample. One without another is useless. To get valid statistic results there's minimal threshold of units, depending on the metods used. For example in veterinary medicine, even if you do see a pattern of new symptoms in clinical setting, a sample of 5 cats may not be enough to provide significant results in research of the same symptoms, or the results wouldn't be reliable. Therefore, researcher would need larger population sample and choosing appropriate sampling frame

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3 Select a sampling method

The third step is to select a sampling method, which is the procedure or technique that you use to select a sample from your sampling frame. There are two main types of sampling methods: probability and non-probability. Probability sampling methods use random selection or chance to ensure that every member of the sampling frame has an equal or known chance of being included in the sample. This reduces the risk of bias and increases the representativeness of the sample. Some examples of probability sampling methods are simple random sampling, stratified sampling, cluster sampling, and systematic sampling. Non-probability sampling methods do not use random selection and rely on other criteria, such as convenience, availability, or judgment, to select the sample. This may introduce bias and limit the representativeness of the sample. Some examples of non-probability sampling methods are convenience sampling, quota sampling, purposive sampling, and snowball sampling.

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4 Determine the sample size

The fourth step is to determine the sample size, which is the number of members of the sampling frame that you include in your sample. The sample size should be large enough to provide sufficient statistical power and precision to detect the effects of your experimental manipulation and to estimate the parameters of your population with confidence. The sample size depends on several factors, such as the level of significance, the effect size, the variability, the design, and the sampling method. You can use formulas, tables, or software to calculate the optimal sample size for your study.

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5 Implement the sampling procedure

The final step is to implement the sampling procedure, which is the process of applying your sampling method and selecting the sample from your sampling frame. You should follow the rules and criteria of your sampling method and document the steps and outcomes of your sampling procedure. You should also assess the quality and representativeness of your sample by comparing its characteristics with those of your population and sampling frame. You should report any limitations or challenges that you faced in selecting your sample and discuss how they may affect your experimental results and conclusions.

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6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Harsh Prakash

Associate - Consulting | YouTube Creator @harshlytix & @guruzlibrary | Business & Artificial Intelligence | Data Science & Visualization Expert | Marketing Analytics | Ex-Piramal, Life-Lab
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Selecting a representative sample in experimental research involves defining the population, creating a sampling frame, choosing an appropriate sampling method (random, stratified, cluster), determining an optimal sample size, employing random selection techniques, stratifying or clustering the population as needed, mitigating sampling biases, ensuring precision and accuracy in the sample's representation, and validating its representativeness against the overall population, all aimed at enhancing the reliability and generalizability of research findings to the broader population under study.

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What are the steps for selecting a representative sample in experimental research?

1

2

3

4

5

6

1 Define the population

2 Choose a sampling frame

3 Select a sampling method

4 Determine the sample size

5 Implement the sampling procedure

6 Here’s what else to consider

Research

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What are the steps for selecting a representative sample in experimental research?

1

2

3

4

5

6

1 Define the population

2 Choose a sampling frame

3 Select a sampling method

4 Determine the sample size

5 Implement the sampling procedure

6 Here’s what else to consider

Research

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