A would be the correct answer:)
Hope this helps!
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:
they are multiplied by 9 on bottom
Step-by-step explanation:
Answer:
Difference = 250 students
Step-by-step explanation:
Let the total number of students be x.
Given the following data;
% driving = 30%
% riding = 60%
% walking = 10%
Number of students driving = 375
First of all, we would determine the total number of students.
Total = 30/100 * x = 375
0.3x = 375
Total, x = 375/0.3
Total, x = 1250 students.
Next, we determine the number of students walking;
Walking = 10/100 * 1250
Walking = 12500/100
Walking = 125 students
Finally, we would determine many more students drive to school than walk to school;
Difference = 375 - 125
Difference = 250 students
Answer:
Step-by-step explanation:
