type 1 and type 2 errors

Question 1

type I error

Answer 1

• Type I errors (the “false positive”): the error of rejecting the null hypothesis given that it is actually true
• reject the null hypothesis, alternative hypothesis accepted
• occurs if probability is too lenient
• e.g. using P>0.10 instead of P>0.05
• e.g. A court finding a person guilty of a crime that they did not actually commit.

Question 2

type II error

Answer 2

• Type II errors (the “false negative”): the error of failing to reject the null hypothesis given that the alternative hypothesis is actually true
• accept null, reject alternative hypothesis
• occurs if probability is too stringent
• e.g. using P>0.01 instead of P>0.05
• e.g., A court finding a person not guilty of a crime that they did actually commit.

Question 3

how could you reduce the chance of a type II error

Answer 3

• set a less stringent/less demanding significance level
• use the 5% level (P>0.05)
• increase the sample size