Insights into the concepts of hypothesis testing (Part 3)

Type I error – Producer’s risk

In continuation to yesterday’s discussion, we don’t have the luxury of knowing the whole population. Unknown population means unknown values of population parameters. But through hypothesis testing, confirmatory inferences about the unknown population parameters can be made. But when we reject a null hypothesis either we make a correct decision of rejecting a false null hypothesis or we make an error of rejecting a true null hypothesis. This error of rejecting a true null hypothesis is called Type I error.  It is a very serious error as committing this error disturbs the “Status Quo”, normally resulting in a loss of significant amount of time and money. This is also called a Producer’s Risk, where a producer rejects a perfectly good lot because of variations in sampling. Producer’s risk is very expensive for the producer as the time and money invested in the lot goes to waste.  The reason behind it is that the product cannot reach the consumer.  The probability of committing this risk is minimized. The probability of committing Type I Error is called level of significance and is denoted by alpha. In the entire hypothesis testing process we fix this risk alpha equal to 0.05 or 0.01. This means that the probability of rejecting a good lot if it ever happens is only 5 in 100 or 1 in 100.