Significance level

Significance level is used to calculate the critical value which is compared with a p-value in order to reject/accept the null hypothesis. It is denoted by α and is a probability threshold below which the null hypothesis is rejected. 

Unlike p-value, the significance level is not a calculated quantity. Instead, it is arrived at through a consensus among the researchers. It is set in advance before the hypothesis testing begins. Conventionally, it is taken to be 1%, 5% or 10% i.e. 0.01, 0.05 or 0.10 respectively.

Significance level also denotes the probability of making a TYPE I error. Type I error is the false rejection of a true null hypothesis. Type II error is the false acceptance of a false null hypothesis.