Type I error, type II error, α and β
In medical setup, Ho is that difference between two treatment groups is not statistically
significant or the observed difference in outcome response between two groups is because of
chance of only. It is framed as outcome response for two groups are same.
A investigator may plan a study with research question that response to new treatment B is
different that response to standard treatment A.
Type I error is rejecting Ho when Ho is true. i.e. concluding that a difference exist when actually
there is no statistically significant difference.
α is probability of committing type I error. It provides a quantification to chance of committing
type I error. While choosing the value of α, an attempt is made to consider a value as small as
possible so one can have a level of confidence (1- α).
Type II error is to fail to reject Ho when it is falls, i.e. to conclude that there exist no difference
when in fact the difference exists. Probability of committing type two error is denoted by β.
Power of study is (1- β), Any investigator wants to maximize the chance of detecting a
difference when the difference truly exists. This chance of detecting the difference when the
difference truly exists is called power of test