Itqualityassurance
Statistical significance is important because it allows researchers to hold a degree of confidence that their findings are real, reliable, and not due to chance.
- When should we note something as statistically significant?
- When to use the 0.01 and the 0.05 level of significance?
- Why is 5% significance level important?
- Why is 0.05 significance good?
When should we note something as statistically significant?
Usually, the significance level is set to 0.05 or 5%. That means your results must have a 5% or lower chance of occurring under the null hypothesis to be considered statistically significant.
When to use the 0.01 and the 0.05 level of significance?
The degree of statistical significance generally varies depending on the level of significance. For example, a p-value that is more than 0.05 is considered statistically significant while a figure that is less than 0.01 is viewed as highly statistically significant.
Why is 5% significance level important?
Why 5%? Note this definition in a well-known dictionary: "Significance level: The level of probability which it is agreed that the null hypothesis will be rejected. Conventionally set at 0.05" (1). Thus, the Cambridge Dictionary of Statistics gives 5% as the definition of the significance level.
Why is 0.05 significance good?
A p-value less than 0.05 (typically ≤ 0.05) is statistically significant. It indicates strong evidence against the null hypothesis, as there is less than a 5% probability the null is correct (and the results are random). Therefore, we reject the null hypothesis, and accept the alternative hypothesis.
