The selection of the analysis method that can be applied depends on the suitability of research and data collection. In addition, there may be limitations in data or sample size due to economic, time and ethical factors. 

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Descriptive statistics provide absolute numbers and do not explain the rationale or rationale behind it. Before applying these statistics, it is important to consider which one is best for your research question and what you want to show. Inferential statistics are complex analyzes that show the relationship between several different variables rather than defining a single variable. They are used when the researcher needs to go beyond absolute values ​​and understand the relationships between variables. These are called bivariate analysis when limited to two variables or multivariate analysis when there are more than two variables.

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If there is a comparative aspect of the study, the sample size depends on how detailed you want the comparison to be. Detecting very small differences requires more samples than detecting large differences. The appropriate sample size also depends on the precision or variability of the data. If a response variable changes slightly from one measurement to another, less samples are needed, and if the rate of change between responses is large, more samples are needed.

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The size and nature of a study should depend on the research content, including the researcher's goals and proposed analysis. We support you to get the best results in questions with such a dynamic structure.