What is a statistical error?

Statistical error is the difference between the estimated or approximated value and the true value.  

Two Possible Types of Statistical Error

Type I Errors occur when we reject a null hypothesis that is actually true; the probability of this occurring is denoted by alpha (a).

Type II Errors are when we accept a null hypothesis that is actually false; its probability is called beta (b).

Example

You test whether a new drug intervention can alleviate symptoms of an autoimmune disease.

A Type I error happens when you get false positive results: you conclude that the drug intervention improved symptoms when it actually didn’t. These improvements could have arisen from other random factors or measurement errors.

A Type II error happens when you get false negative results: you conclude that the drug intervention didn’t improve symptoms when it actually did. Your study may have missed key indicators of improvements or attributed any improvements to other factors instead.

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step-by-step explanation: