The Research Process: Statistical Significance

Statistical Significance
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Statistical Significance
While conducting research, there is a need to ensure that the study results provide a clear picture of what is being studied. The numbers have to make sense or give a clear indication or picture of what is being studied. The term statistical significance mainly denotes or explains that the results generated are attributed to a particular cause. Statistical significance does away with the notion that the results received result from chance or a mere accident. The term gifts the numbers meaning and confirms that the results are a consequence of something.
While describing statistical significance, often researchers will use terms such as strong or weak. While conducting tests, a weak statistical significance denotes that the results cannot be firmly attributed to a particular cause. A strong one denotes the opposite and does away with the notion that luck or chance was involved.
While conducting tests or doing experiments, researchers have to state or indicate what is often known as a significance level. A significance level is a term that denotes or explains the probability that the results of a test or experiment are a consequence of luck or chance. This level has to be determined while conducting a test. To determine the statistical significance, researchers use a value that is denoted as the P-value and compare it with the significance level (Ciapponi et al., 2021). If the p-value is less than the significance level, then the results are considered statistically significant. The opposite is also true.
Statistical significance is indeed crucial and helps researchers answer their research questions with minimal doubt. However, there are instances when the results of a study are...