Determining the number of samples is a crucial step in order to perform reliable analysis. This ensures the purpose of statistical tests and checks if there is no or small margin of error. Justification of the choice of samples is as important as choosing them, since they will be tested for statistical tolerance limits. These samples will be further used to estimate the parameters in any given distribution type. Below are the features of a good sample size:
Since a sample represents a population or universe, the researcher must select the samples based on their characteristics. We consider factors such as level of precision, data required, degree of interpretation and variability for determination.
A sample size needs to be flexible in nature. We reduce the sample size in instances such as availability of information, time and funds.These are non-statistical considerations. We also consider precision under statistical considerations affecting sample size.
Since there is a need to understand which kind of sampling method a research needs, one has to specifically understand the required process of selection of participants. Our expert panel of researchers segregate the sampling methods under random or non-random selection.
Sample units are selected based on the objective of the study excerpting from the elements of the universe. We select the appropriate participants satisfying the purpose of the study and also the requirement in size of the samples.
Defining a sampling frame should be done prior to selecting samples. We list all the units of population constituting the sample frame. This helps you apply the research findings to the population which are defined under the sampling frame.
We combine the help of our statistical analysis tools, our expert subject knowledge and your requirements to determine the necessary size of samples. Statistical power analysis is a hypothesis test to detect existing effects that require assistance by researchers with subject experience.