Question

Which of the following statement is correct? a. Type I errors can only occur if you fail to reject H0. b. Type II errors can only occur when you reject H0. c. When the sample size increases, both the probability of making Type I errors and the probability of making Type II errors can decrease. d. The level of significance is the probability of making a Type II error.

Answer #1

a. Type I errors can only occur if you fail to reject H0= FALSE.

Reason- a. By definition -Type I errors can only occur if you reject H0 when it is true.

b. Type II errors can only occur when you reject H0. =FALSE

Reason- b. By definition- Type II errors can only occur when you fail to reject H0 and not when you reject H0.

C. When the sample size increases, both the probability of making Type I errors and the probability of making Type II errors can decrease = TRUE.

Reason- when we increase the sample size, we decreases the variability of the statistic. This may reduce both types of errors.

d. The level of significance is the probability of making a Type II error. = FALSE.

Reason-The level of significance is the probability of making a Type I error. Significance level is the probability of making the wrog decision when the null hypothesis is actually true.

Describe type I and type II errors for a hypothesis test of the
indicated claim. A shoe store claims that at least 80% of its new
customers will return to buy their next pair of shoes.
Describe the type I error. Choose the correct answer below:
a) A type I error will occur when the actual proportion of new
customers who return to buy their next pair of shoes is no more
than 0.80 but you reject H0: p≤0.80.
b)...

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.

What type of error occurs if you fail to reject (aka "accept")
H0 when, in fact, it is not true?
Question 1 options:
For a given sample size in hypothesis testing,
Question 2 options:
Type II error will not be effected by Type I error.
the smaller the Type I error, the larger the Type II error will
be.
the smaller the Type I error, the smaller the Type II error will
be.
the sum of Type I and Type...

Suppose you have the following null and alternative hypotheses:
H0: μ = 81 and H1: μ ≠ 81.
You collect a sample of data from a population that is normally
distributed . The sample size is 19, the sample mean is 84.9, and
the population standard deviation is 5.7.
What is your p-value and conclusion? Test at a level of
significance of 0.01.
A. 0.0080, Do Not Reject
B. 0.0029, Reject
C. 0.0029, Do Not Reject
D. 0.0064, Reject
E....

You must decide which of two discrete distributions a random
variable X has. We will call the distributions
p0 and p1. Here are the
probabilities they assign to the values x of
X:
x
0
1
2
3
4
5
6
p0
0.1
0.1
0.2
0.3
0.1
0.1
0.1
p1
0.1
0.3
0.2
0.1
0.1
0.1
0.1
You have a single observation on X and wish to test
H0: p0 is correct
Ha: p1 is correct
One possible decision procedure...

Which of the following sentences best characterizes the
relationship among Type 1 error, Type II error, Sample Size, and
the power of hypothesis testing?
hypothesis testing does not rely on sample size, Type I or Type
II error
Type I error is inflated as Type II error decreases, neither is
related to sample size
When the sample size is small, there is a higher chance of
committing a Type II error and decreased power to reject the null
hypothesis
When...

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...

Which of the following statements are TRUE
Note that there may be more than one correct answer; select all
that are true.
a)
The power of a test is only influenced by the hypothesized
parameter value, and not the true parameter value.
b)
For a two-sided alternative hypothesis, as the difference
between the true parameter value and the hypothesized parameter
value increases, the probability of a Type I error increases.
c)
It is desirable to have tests with high power,...

Which of the following statements is (are) not true?
A. The power of the test decreases as the level of
significance decreases.
B. The probability of making a Type II error
increase as the probability of making a Type I error
decreases.
C. The probability of making a Type II error and
the level of significance are the same.
D. All of the above statements are not true
In a criminal trial, a Type II error is made when:
A....

Chapter 4, Section 4, Exercise 139-143
Type I and Type II Errors
In the situation below, describe what it means in that context to
make a Type I and Type II error.
Testing to see whether taking a vitamin supplement each day has
significant health benefits. There are no (known) harmful side
effects of the supplement.
Making a Type I error means:
People should not take any kind of vitamin supplements.
Fail to detect that the supplements are beneficial, when...

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