Type One and Type Two Errors

Yesterday we covered the null and alternative hypothesis, where

the null can be seen as: not guilty
alternative can be seen as: guilty

Because all statistical tests are made with a degree of probability(termed confidence)
there are chances of making errors in our conclusions which can be expressed in two ways:

Type 1 error: Claiming innocence when there is guilt
Type 2 error: Claiming guilt when there is innocence

Example:

Null: IQ doesn't affect school grades
Alternative: IQ affects school grades

Type 1: We conclude IQ does affect grades, when it really doesn't
Type 2: We conclude that IQ does not affect grades, when it really does


There is no need to break your head trying to understand this, just know that whatever conclusion is made from a statistical test, there is always a chance of it being wrong.

As a rule of thumb, science tries to make sure it is correct 1 out of a 100 times. But 1 in 20 and 1 in 10 are also passable.