What is the correct definition of a P-Value?

Probability of as extreme or more extreme assuming Ho is true

Which of the following is an example of a Type I error? (Ho is the assumption that a patient does not have diabetes)

Telling a patient they have diabetes when they don't

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STAT 121 Exam 2

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Questions 15

Answers

1
Which of the follow is an example of correct hypotheses?
Ho: Mu = 25 Ha: Mu ≠ 25
Ho: x-bar = 25 Ha: x-bar > 25
Ho: Mu > 25 Ha: x-bar < 25
Ho: Mu > 25 Ha: Mu < 25
2
beta = probability of failing to reject Ho when false
True
False
3
We want the power of our test to be as high as possible.
False
True
4
observed mean: 13 s: 3.1 n: 50 µ(o): 12 alpha: 0.05 What do we conclude (this is a two-sided test)?
Replicate the hypothesis test
We conclude to give up on statistics and go home :(
Reject Ho
Fail to Reject Ho
5
How do you increase the power of a test?
Decrease alpha
Pray
decrease "effect size"
Increase Sample Size
6
If we have a high p-value, we accept Ho.
False
True
7
All of the following are ways to fulfill the condition of normality except...
The data is randomly selected
Question states that the population is normally distributed
Sample size is greater than 30
The sample plot doesn't have extreme skewness or outliers
8
You are excited for Exam 2!!!
False
True
9
We conduct a hypothesis test assuming that Ho is true.
False
True
10
What is the correct definition of a P-Value?
Assuming Ha is true, the probability of attaining the test statistic
The probability that Ho is true
Probability of as extreme or more extreme assuming Ho is true
The proportion of outliers in a sample
11
Power = 1 - alpha
False
True
12
When we have a low p-value, we reject Ho.
True
False
13
x-bar = 52.3 s = 5.1 n = 45 confidence level = 90% What is our confidence interval?
(51.880, 59.901)
(51.02, 53.58)
(-0.15, 45.72)
(50.3, 54.1)
14
Which of the following is an example of a Type I error? (Ho is the assumption that a patient does not have diabetes)
Telling a patient they don't have diabetes when they do
Telling a patient they have diabetes when they do
Telling a patient they don't have diabetes when they don't
Telling a patient they have diabetes when they don't
15
If a type 1 error is more severe, we want to choose a lower significance level.
False
True

STAT 121 Exam 2 Flashcards | StudBud

STAT 121 Exam 2

15 termsStudBud Administration85 plays

Imported from external platform

Flashcards15 cardsFPractice quizPHost liveL

Questions 15

Answers

1
Which of the follow is an example of correct hypotheses?
Ho: Mu = 25 Ha: Mu ≠ 25
Ho: x-bar = 25 Ha: x-bar > 25
Ho: Mu > 25 Ha: x-bar < 25
Ho: Mu > 25 Ha: Mu < 25
2
beta = probability of failing to reject Ho when false
True
False
3
We want the power of our test to be as high as possible.
False
True
4
observed mean: 13 s: 3.1 n: 50 µ(o): 12 alpha: 0.05 What do we conclude (this is a two-sided test)?
Replicate the hypothesis test
We conclude to give up on statistics and go home :(
Reject Ho
Fail to Reject Ho
5
How do you increase the power of a test?
Decrease alpha
Pray
decrease "effect size"
Increase Sample Size
6
If we have a high p-value, we accept Ho.
False
True
7
All of the following are ways to fulfill the condition of normality except...
The data is randomly selected
Question states that the population is normally distributed
Sample size is greater than 30
The sample plot doesn't have extreme skewness or outliers
8
You are excited for Exam 2!!!
False
True
9
We conduct a hypothesis test assuming that Ho is true.
False
True
10
What is the correct definition of a P-Value?
Assuming Ha is true, the probability of attaining the test statistic
The probability that Ho is true
Probability of as extreme or more extreme assuming Ho is true
The proportion of outliers in a sample
11
Power = 1 - alpha
False
True
12
When we have a low p-value, we reject Ho.
True
False
13
x-bar = 52.3 s = 5.1 n = 45 confidence level = 90% What is our confidence interval?
(51.880, 59.901)
(51.02, 53.58)
(-0.15, 45.72)
(50.3, 54.1)
14
Which of the following is an example of a Type I error? (Ho is the assumption that a patient does not have diabetes)
Telling a patient they don't have diabetes when they do
Telling a patient they have diabetes when they do
Telling a patient they don't have diabetes when they don't
Telling a patient they have diabetes when they don't
15
If a type 1 error is more severe, we want to choose a lower significance level.
False
True