Significance Testing is fundamental in identifying whether there is a relationship exists between two or more variables in a Psychology Research. It is achieved by comparing the probability of which the data has demonstrated its effect due to chance, or due to real connection.
The ‘p’ value in Significance Testing indicates the probability of which the effect is cause by chance. When the p value is small, it suggests that it is likely the effect is not caused by chance. Hence having a real connection between the relationships, and the conclusion we make from the data has higher validity.
The most commonly agreed border in Significance Testing is at the P value 0.05. If the p value is being less than 5% (p<0.05), we will identify it being Statistically Significant. Similarly, if the P value is more than 5% (p>0.05), we will identify it being Statistically Insignificant. However, it is worth knowing that the boarder value of Significance Testing can vary depending on how the experimenter would identify the relationship being significant. In some cases, the experimenters may consider p<0.1 still be Statistically Significant.
Significance Testing is very important in researches as it helps to indicate whether if the data is valid, and the appropriateness to conclude from the data.