Question

1.Type 1 error is...

a.Correctly rejecting the null hypothesis.

b.Rejecting the null hypothesis when it’s actually true.

c.Correctly failing to reject the null hypothesis.

d.Failing to reject the null hypothesis when it’s actually false.

2.Power is defined as the probability of...

a.Correctly rejecting the null hypothesis.

b.Correctly failing to reject the null hypothesis.

c.Failing to reject the null hypothesis when it’s actually false.

d.Rejecting the null hypothesis when it’s actually true.

3. From Study Example 1: Based on the sample, researchers decide to reject the null hypothesis, determining that high school students are sleep deprived. However, additional studies come to the opposite conclusion, finding no evidence of sleep deprivation in high school students.

This is an example of...

a.power.

b.type II error.

c.type I error.

Answer #1

Q1) Type I error happens when we reject a True null hypothesis.
**Therefore Rejecting the null hypothesis when its actually
True is the correct answer here.** Note that is is also
called the level of significance for the test.

Q2) The Power of test is defined as the complement of the type
II error. Power is defined as the probability of correctly
rejecting a False null hypothesis. **Therefore a is the
correct answer here.**

Q3) As we are rejecting the null hypothesis and concluding that
the high schools students are sleep deprived. Although there is no
evidence of sleep deprivation in high school students in reality,
therwfore we are rejecting a true null hypothesis here.
**Therefore Type I error is the required answer
here.**

The primary purpose of hypothesis testing is to attempt to
reject the null hypothesis not to accept the alternative
hypothesis.
True
False
In hypothesis testing, a Type 1 error is
failing to reject the null hypothesis when it is true.
failing to reject the null hypothesis when it is false.
rejecting the null hypothesis when it is true.
rejecting the null hypothesis when it is false.
In general, the power of a statistical test is the probability
that a test...

(1 point)
Type I error is:
A. Deciding the null hypothesis is true when it is
false
B. Deciding the alternative hypothesis is true
when it is false
C. Deciding the null hypothesis is false when it
is true
D. Deciding the alternative hypothesis is true
when it is true
E. All of the above
F. None of the above
Type II error is:
A. Deciding the null hypothesis is false when
it is true
B. Deciding the alternative hypothesis...

Identify the type I error and the type II error for a hypothesis
test of the indicated claim.
The percentage of
households with more than 1households with more than 1
pet
is
greater
than
sixtyfive percent
Identify the type I error. Choose the correct answer below.
A. Reject the null hypothesis that the percentage of
households with more than 1households with more than 1
pet is greater than 65 %
when it is actually true.
B.
Fail to reject the...

1. Setting the significance level cutoff at .10
instead of the more usual .05 increases the likelihood of
a. a Type I error.
b. a Type II error.
c. failing to reject the null hypothesis.
d. accepting the null hypothesis when, in fact, it is false.
2. A Type I error is the result of
a. improper measurement techniques on the part of the
researcher.
b. failing to reject the null hypothesis when, in fact, it is
true.
c. incorrectly...

Identify the type I error and the type II error that correspond
to the given hypothesis.
The percentage of households with more than 1households with
more than 1 pet is less than 65%.
Identify the type I error. Choose the correct answer below.
A.
Fail to reject the null hypothesis that the percentage of
households with more than 1 households with more than 1 pet is
equal to 65%
when that percentage is actually less than 65 %.
B.
Fail...

Type I error is:
A. Deciding the alternative hypothesis is true
when it is false
B. Deciding the alternative hypothesis is true
when it is true
C. Deciding the null hypothesis is true when it is
false
D. Deciding the null hypothesis is false when it
is true
E. All of the above
F. None of the above
Type II error is:
A. Deciding the null hypothesis is false when it
is true
B. Deciding the null hypothesis is true...

A Type I error occurs when __________ and its probability of
occuring is __________.
Select one:
a. we reject a true null hypothesis / alpha
b. we reject a true null hypothesis / 1 - alpha
c. we fail to reject a false null hypothesis / 1 - alpha
d. we fail to reject a false null hypothesis / alpha

9. A Type I error
occurs when we accept a false null hypothesis. true or false

Regarding the definition of Type I and Type II error, which of
the following is correct?
A) Type I error: Fail to reject the null hypothesis when it is
actually false.
B) Type II error: Reject the null hypothesis when it is actually
true.
C) The probability of Type I error is equal to the significance
level.
D) Neither Type I error nor Type II error can be controlled by
the experimenter.

The National Cancer Institute conducted a 2-year study to
determine whether cancer death rates for areas
near nuclear power plants are higher than for
areas without nuclear facilities. A spokesperson
for the Cancer Institute said, "From the data at hand, there was no
convincing evidence of any increased risk of death from any of the
cancers surveyed due to living near nuclear
facilities.” (1 points for each)
Let p denote the proportion of the population in areas
near nuclear...

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