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:
Step-by-step explanation:
In going from (5, 5) to (10, 8), x (the run) increases by 5 and y (the rise) increases by 3. Thus, the slope of the line connecting the first two points is m = 3/5.
In going from (1, 13) to (4, 8), x (the run) increases by 3 and y (the rise) decreases by 5. Thus, the slope of the line connecting the first two points is m = -5/3
Because these results are negative reciprocals of one another, the two lines are PERPENDICULAR to one another.
Simple interest formula: A = P(1 + rt) where P is the Principal amount of money to be invested at an Interest Rate R% per period for t Number of Time Periods. Where r is in decimal form; r=R/100; r and t are in the same units of time.
Since triangle is isosceles, that means that unknown angles are equal. 180-72=108
108:2=54
So you’re answer would be: 54 degrees.
