what s the difference between a type i error and a false positive 
a type i error is often called a false positive this occurs when the null hypothesis is rejected even though it s correct the rejection takes place because of the assumption that there is no relationship between the data sets and the stimuli as such the outcome is assumed to be incorrect the bottom linehypothesis testing is a form of testing that uses data sets to either accept or determine a specific outcome using a null hypothesis although we often don t realize it we use hypothesis testing in our everyday lives this comes in many areas such as making investment decisions or deciding the fate of a person in a criminal trial sometimes the result may be a type i error this false positive is the incorrect rejection of the null hypothesis even when it is true 