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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Step-by-step explanation:
Answer:
C
Step-by-step explanation:
undefined slope means tat the denominator=0 in the equation
m=y2-y1/x2-x1
A: m=-1-1/1+1=-2
B;2-2/2+2=0
C: 3+3/-3+3 = 6/0 undefined
D: 4+4/4+4=1
Answer:
80%
Step-by-step explanation:
28/35 = 0.8
Divide. Convert a decimal to a percent by multiplying times 100.
0.8 × 100 = 80
Tara earned an 80%
You could use a calculator as described above or using mental math or pencil and paper:
28/35 = 4/5
Simplify.
4/5 = 8/10 = 80/100
Percent means per hundred, change 28/35 to hundredths as above.
Tara (still) gets an 80%.
B. Karen only
ice cream : $8 a gallon
$8 times 5 equals $40
paperback novels: $8 each
$8 times 5 equals $40
$40 plus $40 equals $80 and Karen is the only one with $80.
