Statistical Significance Paper. Psychology Assignment

Statistical Significance
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Statistical Significance
Hubbard and Armstrong (2005) state that most scholars consider the significance test as the concluding factor to the whole process of study, and that the statistical significance test directs how scientists articulate their hypothesis. Indeed, during training, scientists are taught that hypothesis is the foundation of every research and that at the most basic level, the null hypothesis is represented by the lack of difference between groups. However, there has been an issue of reproducibility that has been experienced across the globe. The increase in complex systems has led to variations in the effects observed by researchers. The commonly used method of statistical testing to indicate statistical significance is that of the p-value. The p-value was first designed as a means of measuring the strength of the evidence from the research. Although a probability of 0.05 proves that something is significant, it does not mean that the probability should be used as a guide to statistical analysis. When using the Fisher’s model, the p-value is only meant to indicate that the results were not obtained by mere chance, but rather, that a certain level of evidence against the null hypothesis exists. To conclude that the evidence is true based on the p-value would therefore be a misjudgment. Such predictions, by Hubbard and Armstrong, are the conclusion that the meaning of statistical significance is confusing to researchers.
There is also a difference between the two approaches as acknowledged by Fisher and Pearson. The Neyman-Pearson approach is carried out on a fixed position, while the primary objective of Fisher’s method is the statement of a p-value, which in some cases, might not be accompanied by a pronunciation regarding the significanc...