Differences Between Type I Error and Type II Error

Differences Between Type I Error and Type II Error

Type 1 error in tests of statistical hypotheses, refers to the mistake that is caused by refusing to accept a null hypothesis even though it’s true. Type 1 errors occur when a hypothesis that ought to be accepted was rejected. Type I errors are identified by an (alpha) also known as an error. It is also known as the significance level that the tests. This type of error can be described as a false negative error in which it is impossible to prove the hypothesis due to an error in the test.

⚠️
  1. Click on your ad blocker icon in your browser's toolbar
  2. Select "Pause" or "Disable" for this website
  3. Refresh the page if it doesn't automatically reload