A type 1 error means that the experimental /alternative hypothesis has been accepted when the null hypothesis should have been retained. A type two error means that the null has been retained when the experimental/alternative should have been accepted and the null rejected. These errors can occur if the wrong level of significance is used. For example p<0.01 means we are being too cautious and may make a type 2 error. If we use p<0.1 then we are being too relaxed and run the risk of making a type 1 error.