Question

Would increasing the significance level of a hypothesis test increase or decrease the likelihood of a researcher making a Type I error?

Answer #1

___ non-directional test
___ directional test
___ alpha
level
___ null hypothesis
___ alternative
hypothesis e.
___ rejection range
___
inferential
___
inference
___ significance tests
___ statistical power
a. The hypothesis that is rejected or retained using inferential
statistics and is often the opposite of what the researcher
believes to be true.
b. The researcher hypothesizes that a given score will be either
higher or lower than the chosen level of significance.
c. The likelihood of rejecting the null hypothesis...

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...

Setting the significance level cutoff at .10 instead of the more
usual .05 increases the likelihood of A. a Type I error. B.
accepting the null hypothesis when, in fact, it is false. C. a Type
II error. D. failing to reject the null hypothesis.

A hypothesis test is to be performed with a Null hypothesis
Ho: µ ≥ 15 and an alternative
hypothesis H1: µ <
15, the population standard deviation
is σ=2.0, the sample size is;
n=50, and the significance level is
α=0.025.
1- What is type l error?
2- What is the chance of making a type I error in the above
test?
3- What is a Type II error?
4- What value would the sample mean have to be less than to...

Typically, when we decrease the probability of a type I error
for a hypothesis test, we:
decrease the probability of a type II error
increase the probability of a type II error

Consider the following statements.
(i) If a hypothesis is tested at the 5% significance level with
a given data set, then there is a lower chance that the null
hypothesis will be rejected than if that same hypothesis is tested
at the 1% significance level with the same data set.
(ii) P(Type I Error) + P(Type II Error) =
1.
(iii) If a hypothesis test is performed at the 5% significance
level, and if the alternative hypothesis is actually true,...

A significance test about a proportion is conducted using a
significance level of 0.025. The test statistic equals 1.33. The
P-value is 0.10. a. If Upper H 0 were true, for what probability
of a Type I error was the test designed? b. If this test resulted
in a decision error, what type of error was it?
a. If Upper H 0 were true, for what probability of a Type I
error was the test designed?
b. If this test...

1. A hypothesis test is conducted with a significance level of
5%. The alternative hypothesis states that more than 65% of a
population is right-handed. The p-value for the test is calculated
to be 0.03. Which of the following statements is correct?
A .We can conclude that more than 3% of the population is
right-handed.
B .We cannot conclude that more than 65% of the population is
right-handed.
C .We can conclude that more than 65% of the population is...

If the probability of a type II error in a hypothesis test is
0.07, what is the power of the hypothesis test? Assuming your
sample is unbiased, would increasing the size of the sample
increase or decrease the power of the hypothesis test? Please
explain your answer.

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...

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