Type 1 Error
A type one error is where the null hypothesis is rejected when infact it was true.
For example; A pregnancy test comes up as positive and so we immediately see ourselves as pregnant and reject the null hypothesis that we are not. There is a 0.01% chance that we arent pregnant- this is ignored despite it being true.
This is known as a type 1 error
Type 2 error
A type 2 error is when the Null hypothesis is accepted and but it is false.
With reference back to the pregnancy thing ( It seriously was the only example I could think of )
In this case, the result of the test could say we weren't pregnant when infact we are. This leads us to accept the null hypothesis that we are not pregnant when it isnt true.