The level of significance is statistical concept that refers to the probability of rejecting the null hypothesis when it is actually true. The null hypothesis IS a statement that there is no significant difference between two or more variables, while the alternative hypothesis is a statement that there is a significant difference. The level of significance is usually denoted by alpha (É‘) and is typically set at 0.05 or 0.01.

When conducting hypothesis
testing, the level of significance is used to determine whether the results of
a statistical test are statistically significant or not. If the p-value
(probability value) of the test is less than the level of significance, the
null hypothesis is rejected, and the alterative hypothesis is accepted.
Conversely, if the p-value is greater than the level of significance, the null
hypothesis is not rejected.

The level of significance is an
important concept in statistical analysis because it helps to control for the
likelihood of making a type error (rejecting the null hypothesis when it is actually
time). By setting a specific level of significance, researchers can ensure that
their findings are reliable and valid.