Type I error is:
" Reject the claim that the proportion of people who write with their left hand is 0.29 when the proportion is actually 0.29 "
Type II error is:
"Fail to reject the claim that the proportion of people who write with their left hand is 0.29 when the proportion is actually different from 0.29 "
<u>What is proportion?</u>
An equation in which two ratios are made equal is called a proportion. For instance, you could write the ratio as 1: 3 (for every one boy, there are three girls), which means that 14 of the population is made up of boys and 34 of the population is made up of girls.
In Statistics, a type I error is the rejection of a true null hypothesis
and a type II error is the non-rejection of a false null hypothesis
Given that p = 0.29 is accepted
Now type I error is
C. Reject the claim that the proportion of people who write with their left hand is 0.29 when the proportion is actually 0.29
i.e. (false positive)
and type II error here is
B. Fail to reject the claim that the proportion of people who write with their left hand is 0.29 when the proportion is actually different from 0.29.
To learn more about the proportion from the given link
brainly.com/question/19994681
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P(TeamA) = 0,43
P(Female) = 0,52
P(TeamA and Female) = 0,19
P(TeamA or Female) = ?
P(TeamA or Female) = P(TeamA) + P(Female) - P(TeamA and Female) <=>
P(TeamA or Female) = 0,43 + 0,52 - 0,19 <=>
P(TeamA or Female) = 0,76 or 76%
Answer: what u mean lol
Step-by-step explanation:
