Quantitative Methods 2017

Two types of errors in statistical inference

• The null hypothesis is true, but you reject it • An improbable event has occurred • The probability is controlled through the significance level - Type I error - False positive • The probability is a (usually set to 5%) • The null hypothesis is false, but you accept it • The result was not ‘extreme enough’ • Sample size not sufficient - Type II error - False negative • The probability is denoted b . • It is closely related to power , 1- b