R Programming for Statistics and Data Science - Type I and Type II Errors

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Information Technology (IT), Architecture
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University
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Hard
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5 questions
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1.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is a Type 1 error in hypothesis testing?
Accepting a false null hypothesis
Rejecting a true null hypothesis
Rejecting a false null hypothesis
Accepting a true null hypothesis
2.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
In the monster hunting analogy, what does yelling 'demo dog' when there is no monster represent?
A false alarm
A Type 1 error
A Type 2 error
A correct decision
3.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What does beta represent in the context of Type 2 errors?
The probability of accepting a false null hypothesis
The probability of rejecting a false null hypothesis
The probability of accepting a true null hypothesis
The probability of rejecting a true null hypothesis
4.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
How can researchers increase the power of a test?
By decreasing the sample size
By increasing the sample size
By increasing the significance level
By reducing the significance level
5.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is the power of a test in statistical terms?
The probability of rejecting a false null hypothesis
The probability of accepting a false null hypothesis
The probability of rejecting a true null hypothesis
The probability of accepting a true null hypothesis
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