Wednesday, March 20, 2013

Type I or Type II?

The following table has helped me avoid confusing Type I and Type II errors. Write the true hypothesis numbers on the left, and the ones announced on top.

Announced 0
Announced 1
Actually 0
No error
Type I
Actually 1
Type II
No error

Now read out the row and column headers as a binary number:

  • 01 (which is 1 in binary) means H0 was true and we announced H1. That is error Type I.

  • 10 (which is 2 in binary) means H1 was true and we announced H0. That is error Type II.

(Or, perhaps, it is easier to remember that Type I is a false alarm and Type II is a miss.)

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