The probability of type II error will decrease if the level of significance of a hypothesis test is raised from 0.005 to 0.2.
<h3 /><h3>What is a type II error?</h3>
A type II error occurs when a false null hypothesis is not rejected or a true alternative hypothesis is mistakenly rejected.
It is denoted by 'β'. The power of the hypothesis is given by '1 - β'.
<h3>How the type II error is related to the significance level?</h3>
The relation between type II error and the significance level(α):
- The higher values of significance level make it easier to reject the null hypothesis. So, the probability of type II error decreases.
- The lower values of significance level make it fail to reject a false null hypothesis. So, the probability of type II error increases.
- Thus, if the significance level increases, the type II error decreases and vice-versa.
From this, it is known that when the significance level of the given hypothesis test is raised from 0.005 to 0.2, the probability of type II error will decrease.
Learn more about type II error of a hypothesis test here:
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Answer:
The reason for the columns adding up to 1 is that each individual consumes a proportion or a fraction of the total quantity produced under each product category and every product is consumed. There is no leftover.
When the proportions of all the individuals are added up, the sum is always 1 under each product category because each individual can only consume a part of the whole.
Step-by-step explanation:
a) Data and Calculations:
Food Clothes Housing Energy High Quality 100
Proof Moonshine
Farmer 0.25 0.15 0.25 0.18 0.20
Tailor 0.15 0.28 0.18 0.17 0.05
Carpenter 0.22 0.19 0.22 0.22 0.10
Coal Miner 0.20 0.15 0.20 0.28 0.15
Slacker Bob 0.18 0.23 0.15 0.15 0.50
Total 1.00 1.00 1.00 1.00 1.00
Answer:
Step-by-step explanation:
the areas are the same, the outer squares of Q are the ones missing in the center
Answer:
I think the answer is A
Step-by-step explanation:
So sorry if the answer is incorrect
