Alpha level

Alpha level (also known as the significance level) is a probability threshold used to determine whether to accept or reject a null hypothesis.

It is typically set at 0.05 and is used to decide if the observed difference in a study is statistically significant or not.

How to calculate

  1. Start by stating the null hypothesis, which is the statement that there is no difference between the two groups being compared in the study.

  2. Set the alpha level (also known as the significance level), which is a probability threshold used to determine whether to accept or reject the null hypothesis. This is typically set at 0.05.

  3. Calculate the test statistic and the associated p-value.

  4. Compare the p-value to the alpha level.

  5. If the p-value is less than the alpha level, then reject the null hypothesis and accept the alternative hypothesis. This means that there is a statistically significant difference between the two groups.

  6. If the p-value is greater than the alpha level, then fail to reject the null hypothesis. This means that there is not a statistically significant difference between the two groups.

Examples

  1. Alpha level is commonly used in hypothesis testing to determine the level of statistical significance. For example, if the alpha level is set to 0.05, any p-value less than 0.05 would indicate the result is statistically significant.

  2. Alpha level is also used to compare the results of two different groups in an experiment. For instance, if the alpha level is set to 0.01, the results of two groups must have a p-value of less than 0.01 to be considered statistically significant.

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