Exam 1

1. Metainformation

   Tag	Value
   file	Inferential_Statistics_vufsw-type_I_error-1245-en_vufsw-type_I_error-1245-en
   name	vufsw-type I error-1245-en
   section	inferential statistics/nhst/statistical errors/type I error
   type	schoice
   solution	TRUE, FALSE, FALSE, FALSE
   Type	conceptual
   Program	NA
   Language	English
   Level	statistical reasoning

   Question

   Suppose we use a significance level of 5% for testing our hypothesis. If we wrongly reject the null hypothesis, then …

   
   
   1. TRUE: We are going to make a Type I error. The probability of this error is 5%
   2. FALSE: We are going to make a Type II error. The chance of this error is always unknown.
   3. FALSE: We are going to make a Type I error. The chance of this error is always unkown.
   4. FALSE: We are going to make a Type II error. The probability of this error is 5%
   
   

   Solution

   We are going to make a type I error. The probability of this error is 5%. A type I error is the rejection of a true null hypothesis (also known as a “false positive” finding), while a type II error is failing to reject a false null hypothesis (also known as a “false negative” finding).^[1] More simply stated, a type I error is to falsely infer the existence of something that is not there (confirming to common belief with false information), while a type II error is to falsely infer the absence of something present (going against the common belief with false information).

   M&T Hypothesis testing: means
   Default value

   M&T Hypothesis testing: proportions
   Default value

   
   
   1. True
   2. False
   3. False
   4. False