"Within a hypothesis test, a type I error is the error of incorrectly rejecting a null hypothesis when it is true." (Glenn J Myatt, "Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining", 2006)
"A type of error used in hypothesis testing that arises when incorrectly rejecting the null hypothesis, although it is actually true. Thus, based on the test statistic, the final conclusion rejects the Null hypothesis, but in truth it should be accepted. Type I error equates to the alpha (α) or significance level, whereby the generally accepted default is 5%." (Lynne Hambleton, "Treasure Chest of Six Sigma Growth Methods, Tools, and Best Practices", 2007)
"A term that refers to incorrectly rejecting a null hypothesis. It is also sometimes termed a false positive. It is used when an outcome is incorrectly identified as having happened, such as when a customer is incorrectly identified as having committed fraud." (Evan Stubbs, "Delivering Business Analytics: Practical Guidelines for Best Practice", 2013)
"Rejection of the null hypothesis when it's true." (Geoff Cumming, "Understanding The New Statistics", 2013)
"Probability of rejecting the null hypothesis when the null hypothesis is true." (K N Krishnaswamy et al, "Management Research Methodology: Integration of Principles, Methods and Techniques", 2016)
"Probability of rejecting the null hypothesis when it's true." (Geoff Cumming, "Understanding The New Statistics", 2013)
No comments:
Post a Comment