Experimental errors occurs in the execution of experiment design. Example of experimental errors are mistakes in data entry, systematic error, and random error caused by environmental conditions. Did you even heard about type I and type II error? Because that may be the 2 ways you are looking for.
A false positive is called a Type I error, and it is the type of error that incorrectly rejecting the null hypothesis in the favor of the alternatives.
A false negative is what you called Type II error, it is the opposite of type I error and it is the false acceptance of the null hypothesis. A type II errors are not seen to be as problematic as type I error, type I error is more serious than type II error, because you have wrongly rejected the null hypothesis.
