Question

In a hypothesis testing problem, the observed level of significance is:

A) the probability of not rejecting the null hypothesis when it is false

B) the confidence level of the associated interval estimation problem

C) one minus the confidence level of the associated interval estimation problem

D) the probability of rejecting the null hypothesis when it is true

E) the probability, calculated under the null hypothesis of obtaining a random sample of the same size containing even stringer evidence against the null hypothesis than is contained in the data sample

Answer #1

In a hypothesis testing problem, the observed level of significance is the probability of rejecting the null hypothesis when it is true.

Explanation:

Level of significance is probability of type 1 error.

Type 1 error is rejecting the null hypothesis when it is true.

And the probability of type 1 error is level of significance.

Therefore level of significance is the probability of rejecting the null hypothesis when it is true.

Note that size of the test does not exceed level of significance. In many cases they are equal.

For each problem,
select the best response.
(a) The P -value of a test of a null hypothesis
is
A. the probability the null hypothesis is
false.
B. the probability, assuming the null hypothesis
is false, that the test statistic will take a value at least as
extreme as that actually observed.
C. the probability, assuming the null hypothesis
is true, that the test statistic will take a value at least as
extreme as that actually observed.
D. the probability...

For each problem, select the best response.
(a) In formulating hypotheses for a statistical test of
significance, the null hypothesis is often
A. a statement that the data are all 0.
B. a statement of ''no effect'' or ''no
difference''.
C. the probability of observing the data you
actually obtained
D. 0.05
(b) In testing hypotheses, which of the following would be
strong evidence against the null hypothesis?
A. Obtaining data with a large P
-value.
B. Using a small...

The null hypothesis in
a hypothesis test refers to _____________.
Multiple Choice
the level of
significance
the default state of
nature or status quo
the probability of
rejecting the alternative hypothesis when it is false
a particular
population parameter specified with the sign ≠

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...

In a hypothesis testing problem, the decision as to whether the
null hypothesis should be rejected or not can be made by comparing
the level of significance and the observed level of significance.
The null hypothesis should be rejected if:
A) the level of significance is bigger than the (nonzero)
observed level of significance
B) the level of significance is equal to one half of the
(nonzero) observed level of significance
C) the level of significance is smaller than the...

In hypothesis testing, what is the level of significance?
SELECT ALL CORRECT OPTIONS
OPTION A
A value between 0 and 1.
OPTION B
The risk of rejecting the null hypothesis when it is true.
OPTION C
It is selected before a decision rule can be formulated.
OPTION D
All apply.

R2.30: In hypothesis testing, the Null hypothesis is:
A. Influencing the level of significance for the test
B. Accepted when the test statistic falls within the rejection
region
C. Used to calculate the test statistic
D. An assumption that is claimed to be true

1. The P-value of a test of the null hypothesis is
a. the probability the null hypothesis is true.
b. the probability the null hypothesis is false.
c. the probability, assuming the null hypothesis is false, that
the test statistic will take a value at least as extreme as that
actually observed.
d. the probability, assuming the null hypothesis is true, that
the test statistic will take a value at least as extreme as that
actually observed.
2. The P-value...

Suppose you want to test H0: u
<=100 against H1: u>
100 using a significance level of 0.05. The population is normally
distributed with a standard deviation of 75. A random sample size
of n = 40 will be used. If u = 130, what
is the probability of correctly rejecting a false null hypothesis?
What is the probability that the test will incorrectly fail to
reject a false null hypothesis?

(a) Name the t test used in hypothesis testing to
evaluate the mean observed in one sample.
(b) Who determines the level of confidence for an interval
conservative?

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