Question

Consider the following statements.
Determine which of the above statements are true (1) or false (2). So, for example, if you think that the answers, in the above order, are True,False,False, then you would enter '1,2,2' into the answer box below (without the quotes) |

Answer #1

Consider the following statements.
(i) The smaller the p-value, the stronger the evidence
is in favor of the null hypothesis.
(ii) The p-value forms the borderline between values
of the test statistic that would result in rejecting the null
hypothesis and values of the test statistic that would result in
not rejecting the null hypothesis.
(iii) The p-value is calculated under the assumption
that the null hypothesis is true.
Determine which of the above statements are true (1) 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.

(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...

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...

In a two-tailed hypothesis test of the mean using a 0.05 level
of significance, researchers calculated a p-value of 0.03. What
conclusion can be drawn? The alternative hypothesis should be
rejected because the p-value is so small. The null hypothesis is
true because the p-value is less than the level of significance.
The alternative hypothesis is 3% likely to be true. The null
hypothesis should be rejected because the p-value is less than the
level of significance.
1.The alternative hypothesis...

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...

When the following hypotheses are being tested at a level of
significance of α
H 0 : μ >= 500
H a : μ < 500
the null hypothesis will be rejected if the p -value
is
a.< (underlined) a
b. > a
c. >a/2
d. < (underlined) 1 - a/2

In a Bonferonni Multiple Comparison method, the significance
level on each hypothesis test
A. will change depending on how many group means are
different.
B. needs to be increased so that there is less chance of making
a Type I Error.
C. is always set at 0.05.
D. needs to be reduced so that the probability of making at
least one Type I Error remains at something reasonable, such as
0.05.
E. needs to be reduced so that there is...

Which of the following are true statements? I. If there is
sufficient evidence to reject a null hypothesis at the 5% level,
then there is sufficient evidence to reject it at the 1% level. II.
Whether to use a one- or two-sided test is typically decided after
the data are gathered III. If a hypothesis test is conducted at the
1% level, there is a 1% chance of rejecting the null hypothesis

Please answer True or False for the following statements:
1.) In hypothesis testing, if the null hypothesis is rejected,
then the alternative or motivated hypothesis must also be
rejected.
2.) Under certain conditions, binomial distributions can be
approximated by normal distributions.
3.) Using a normal distribution to approximate binomial
probabilities is extremely accurate, but takes an excessive amount
of time and should be avoided.
4.) A bell-shaped curve is still normal, even if the mean,
median, and mode are not...

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