Answer:
I'm guessing the answer is B againn XD
must be a lucky day for B!!
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:
Write the problem as a mathematical expression.
X=−1/5; f(x)=(25/2)x+(−91/2)
Replace the variable x with x=−1/5 in the expression.
f(−1/5)=(25/2)(−1/5)−91/2
Simplify the result.
−48
Step-by-step explanation:
The product is a bit less than the estimate. In fact, 7.69 is less than 8, and if you start with an equality, i.e.
you can multiply both sides by a positive number, and the inequality will still hold:
6 divided by some number.
