Choosing
appropriate statistical tests is crucial but deciding which tests to use can be
challenging. Different tests suit different types of data and research
questions, so it is important to choose the right one. Knowing how to select an
appropriate test can lead to more accurate results. Invalid results and
misleading conclusions may be drawn from a study if an incorrect statistical
test is used. Therefore, to avoid these it is essential to understand the
nature of the data, the research question, and the assumptions of the tests
before selecting one. This is because there are a wide variety of tests
available. This paper provides a step-by-step approach to selecting the right
statistical test for any study, with an explanation of when it is appropriate
to use it and relevant examples of each statistical test. Furthermore, this
guide provides a comprehensive overview of the assumptions of each test and
what to do if these assumptions are violated.
References
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Trajkovski, V. (2016) How to Select Appropriate Statistical Test in Scientific Articles. Journal of Special Education and Rehabilitation, 17, 5-28.
https://doi.org/10.19057/jser.2016.0
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Upadhyay, H.P. (2017) How to Choose the Statistical Technique in the Data Analysis. International Journal of Research Studies in Biosciences, 5, 33-37.
https://doi.org/10.20431/2349-0365.0505005
[3]
Kim, N., Fischer, A.H., Dyring-Andersen, B., Rosner, B. and Okoye, G.A. (2017) Research. Techniques Made Simple: Choosing Appropriate Statistical Methods for Clinical Research. Journal of Investigative Dermatology, 137, e173-e178.
https://doi.org/10.1016/j.jid.2017.08.007
[4]
Siegel, S. (1956) Nonparametric Statistics for the Behavioral Sciences. McGraw-Hill, Singapore.
Pembury Smith, M.Q. R. and Ruxton, G.D. (2020) Effective Use of the McNemar Test. Behavioral Ecology and Sociobiology, 74, Article No: 133.
https://doi.org/10.1007/s00265-020-02916-y