Assignment: Evaluating Significance of Findings

Statistical Significance and Meaningfulness

A research paper claims a meaningful contribution to the literature based on finding statistically significant relationships between predictor and response variables. In the footnotes, you see the following statement, “given this research was exploratory in nature, traditional levels of significance to reject the null hypotheses were relaxed to the .10 level.”

Statistical significance deals with a critical value of a statistic and making a determination of whether the null hypothesis is rejected or you fail to reject the null hypothesis (Laureate Education (Producer), 2016f). Meaningfulness is the taking that statistic and determining its applicability out in the real world (Laureate Education (Producer), 2016f).

The statement “given this research was exploratory in nature, traditional levels of significance to reject the null hypotheses were relaxed to the .10 level,” The statement notates that a qualitative research study was completed using the exploratory research tool, and exploratory research is often used to generate formal hypotheses. Formal hypotheses is an idea which is suggested as a possible explanation of a particular situation or condition, but which has not yet been proved to be correct. The traditional level of significance is the probability of rejecting the null hypothesis in a statistical test when it is true. Null hypothesis contradicts the research hypothesis and states that there is no difference between the population means and some specified value (p-value). The p-value threshold is <0.05 which is extremely strict; therefore, to reduce the extreme strictness by relaxing the p-value to <0.10. The predictability is greater in weakness.

References

Laureate Education (Producer). (2016f). Meaningfulness vs. statistical significance [Video file]. Baltimore, MD: Author.