Question

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 rejecting the null hypothesis.

d. incorrectly accepting the null hypothesis.

3. Setting the significance level at a very extreme
cutoff (such as .001) increases the chances of

a. getting a significant result.

b. rejecting the null hypothesis.

c. a Type I error.

d. a Type II error.

4. Failing to reject the null hypothesis when the
research hypothesis is true is referred to as

a. the probability of rejection.

b. the error term.

c. a Type I error.

d. a Type II error.

5. Type II errors concern scientists because

a. it could mean that a good theory or beneficial practice is not
used.

b. it means that the experiment must be repeated to confirm the
positive result.

c. rejecting the null hypothesis should only occur when the
research hypothesis is true.

d. future researchers might build entire theories based on a
mistakenly significant result.

need asap please

Answer #1

Solution:

1. Setting the significance level cutoff at .10 instead of the more usual .05 increases the likelihood of

Ans : a Type I error.

Option : a

2. A Type I error is the result of

Ans : incorrectly rejecting the null hypothesis

Option : c

3. Setting the significance level at a very extreme cutoff (such as .001) increases the chances of

Ans : a Type II error.

Option : d

4. Failing to reject the null hypothesis when the research hypothesis is true is referred to as

Ans : a Type I error

Option : c

5. Type II errors concern scientists because

Ans : it could mean that a good theory or beneficial practice is not used.

Option : a

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.

2. A research team hypothesizes that setting weekly
scheduled online interactions versus not setting such interactions
can boost the wellbeing of people who are living on their own
during the stay at home order.
c. How would committing a Type II error translate to
this research question? Discuss both aspects involved in the
process of committing a Type II error with regards to this
particular question. Your answer should look something like “A Type
II error would be committed if...

1.Type 1 error is...
a.Correctly rejecting the null hypothesis.
b.Rejecting the null hypothesis when it’s actually true.
c.Correctly failing to reject the null hypothesis.
d.Failing to reject the null hypothesis when it’s actually
false.
2.Power is defined as the probability of...
a.Correctly rejecting the null hypothesis.
b.Correctly failing to reject the null hypothesis.
c.Failing to reject the null hypothesis when it’s actually
false.
d.Rejecting the null hypothesis when it’s actually true.
3. From Study Example 1: Based on the sample,...

1. A null hypothesis states that there is
A. No significant difference between a population parameter and
sample statistic.
B. A significant difference between a population parameter and
sample statistic.
C. The difference between the population parameter and sample
statistic is significant and can be attributed to sampling
error.
D. The difference between the population parameter and sample
statistic is insignificant and cannot be attributed to sampling
error.
E. None of the above
2. An alternative hypothesis states that there...

If a directional, .05 level of significance (predicted ‘lower
than’) had been chosen, what z-score would be needed for the
difference between X and µ to be significant?
A. -1.65
B. -1.96
C. -2.33
D. +/- 1.65
If the probability of finding a difference that really does
exist is .65 (correctly rejecting the null hypothesis when the null
hypothesis really is false), what is the probability of the Type II
error?
A. .05 B. .95 C. .35 D. .65 also

When you incorrectly reject the null hypothesis and claim there
are significant differences between your two means, and no such
difference exists in the population, you have a(n)______
Type I Error
Unstandardized effect size
Type II Error
There is not enough information given to determine
A Type II Error occurs when you fail to reject the null hypothesis
when it is true
True or False

ohn ran an experiment and found the "t" value to be significant
at the .05 level. In actual fact the null hypothesis is true. What
error has John committed and what are his chances of doing so?
Type I error; 1 chance in 20.
Type I error; 1 chance in 100.
Type II error; 1 chance in 20.
Type II error; about 85% chance

You complete a hypothesis test using a = .05, and based
on the evidence from the sample, your decision is to reject the
null hypothesis. If the treatment actually has no effect, which of
the following is true?
Group of answer choices
You have made a Type I error.
You have made a Type II error.
You might have made a Type I error, but the probability is only
5% at most.
You have made the correct decision.
For a...

Question 1 : The answers listed below are characteristics of a
Type I error EXCEPT for one. Select the characteristic that is not
for Type I error
a) upsetting status quo for falsehood
b) a 'missed opportunity'
c) reject null hypothesis with null is true
question 2: The answers listed below are characteristics of a
Type II error EXCEPT for one. Select the characteristic that is not
for Type II error
a) do not reject null hypothesis when it is...

The National Cancer Institute conducted a 2-year study to
determine whether cancer death rates for areas
near nuclear power plants are higher than for
areas without nuclear facilities. A spokesperson
for the Cancer Institute said, "From the data at hand, there was no
convincing evidence of any increased risk of death from any of the
cancers surveyed due to living near nuclear
facilities.” (1 points for each)
Let p denote the proportion of the population in areas
near nuclear...

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