What is the difference between type I vs type II error?
Type I error is equivalent to a False positive. Type II error is equivalent to a False negative. Type I error refers to non-acceptance of hypothesis which ought to be accepted. Type II error is the acceptance of hypothesis which ought to be rejected.
ref:What is better- a Type I or a Type II error? | by Vimarsh Karbhari | Acing AI | Medium