Question

TRUE/FALSE. Explain.

1.) Power + B (beta) = 1

2.) You can increase power and decrease (Alpha) at the same time by increasing sample size.

3.) alpha= 1- beta

4.) alpha is the significance level and the probability of type II error

5.)Type II error is rejection the null when the null is true.

6.)There is more than one way to increase power.

7.)Statistical significance implies practical significance.

Answer #1

(1) TRUE because power = 1- beta or power + beta= 1

(2) FALSE, because power and alpha are directly proportional to sample size, i.e. when sample size increases, both power and alpha increases and vice versa

(3) FALSE, because alpha is not equal to 1 -beta, but power = 1-beta

(4) False, because alpha is the probability of type I error

(5) False, rejecting the null hypothesis when it is true is type 1 error

(6) TRUE, we can increase power by sample size, significance level, etc.

(7) False, statistical significance never implies pratical significance

Question 1 (1 point)
True or False:
The power of a test is the probability of rejecting the null
hypothesis when the null is false.
Question 1 options:
True
False
Question 2 (1 point)
What type of error occurs when a false null hypothesis is not
rejected?
Question 2 options:
Type I
Type II
Type III
Rejection Error
Question 3 (1 point)
Which type of error results in a "false alarm?"
Question 3 options:
Type I
Type II
Type III...

Explain how number of subjects, effect-size, and statistical
power are related.
- Imagine there is a true effect, state how increasing the
number of subjects can influence statistical power?
- If the number of subjects are held constant, state how an
increase in the size of the true effect influences statistical
power.
- Explain how the type II error rate is different from the type
I error rate.
- State how increasing statistical power influences the type II
error rate.

It is not possible to use ANCOVA to increase statistical power,
only decrease it.
True
False

true or false:
1) if alpha is made more stringent, beta increases
2) if a result is statistically significant, it must be an
important result
3) by using a stringent alpha level and designing the
experiement for high power, we maximizes the probability of
correctly concluding regardless of whether H0 is true or
false

Which one of the following statements is
FALSE?
a.
The p-value gives an indication of how close our estimate is to the
hypothesized value of the parameter.
b.
Assume the level of significance for a test and the effect size of
interest are both fixed. Then, increasing the sample size will
decrease P[Type2 error].
c.
When the null hypothesis is TRUE, P[Type 1 error] = the level of
significance of the test (alpha)
d.
The p-value is a conditional probability....

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....

True or False: Null and Alternative Hypotheses can never refer
to sample statistics.
True or False: Type I error and Type II error canbothbe
controlled by increasing the sample size.
True or False: The pooled variance t-test can never be used when
you have dependent sampling.

1 The probability of type II error becomes bigger if the level
of significance is changed from 0.01 to 0.05.
True
False
2
Increasing the sample size reduces the probability of committing
a Type I and Type II simultaneously.
True
False
3
In testing a hypothesis about a population mean with an unknown
population standard deviation (σ ) the degrees of freedom
is used in the denominator of the test statistic.
True
False
4
When a researcher fails to reject...

Indicate whether each of the following five statements are True
or False.
1) A large p-value indicates the null hypothesis must be
true.
2) Increasing the confidence level decreases the sample size needed
to achieve a desired margin of error.
3) Increasing the sample size decreases the power of a hypothesis
test.
4) Increasing the significance level increases the power of a
hypothesis test.
5) If the interaction term in a two factor experiment is
significant (small p-value), the main...

1) A researcher wishes to perform a hypothesis test in order to
determine whether there is evidence that the mean family income in
the U.S. is different from $30,000. The rejection region of the
corresponding hypothesis test will be: (Circle one)
a) Located in the right tail of the sampling distribution
b) Located in the left tail of the sampling distribution
c) Located in both the left and right tails of the sampling
distribution
d) Centered around the mean of...

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