Use your textbook to answer each of the questions below. We only have 3
days to review this stuff, so you have to teach yourself the foundational
terms/concepts yourself—via these questions!
1.)
The chapter starts off with an example of a
hypothesis test regarding “therapeutic touch.”
a.
First, read the context—page 473-474 (stop when
you get to the ESP? bullet)
b.
Now, look at the “step by step” example on the
bottom of page 474:
i.
Record the null and alternative hypotheses for
this problem:
ii.
Read through the conditions.
iii.
Show the math work for this problem—don’t just
copy it from the book, write it out as we would: show the z-score with its
formula, the Normal model, and p-value. (All of this information is already
show, you just have to organize it as we would).
iv.
The p-value for this problem is 0.788. In our
null hypothesis, we are assuming this person is not capable of therapeutic
touch. Our alternative suggests that
this person is capable of therapeutic touch. Use this wording/context
and our “writing template” to write an appropriate conclusion for this test.
2.)
What is a p-value?
Record the definition of p-value—highlighted in blue on page 476.
3.)
Below this blue section there is a sentence in
italics (on p. 476). Copy this sentence below!
4.)
Record the highlighted blue text on the top half
of page 477.
5.)
Now, read the bottom of page 477, “Alpha
Levels.” This references alpha levels and statistical significance; record the
blue statement on the bottom of p. 477, and the blue section on the top of p.
478.
6.)
Much of this chapter delves deeper into the
details about hypothesis testing. However, we are going to introduce two new
ideas: type I and type II error!
a.
What is a type
one error? (read the bottom of p. 482)
b.
What is/define a type two error.
7.)
An alpha level represents the “cutoff” value we
use to decide if we reject the null hypothesis—but it’s also connected to Type
I error. How so? Look at one of the blue highlighted pieces on page 483 and
state how alpha relates to Type I error.
8.)
What is the power
of a test? (blue stuff on page 483 AND on p. 484).
a.
Read the entire section about power on p. 484!
9.)
How do we calculate
power? (look at the bullets on p. 487)
10.) What
is effect size? (p. 485)
11.) There
are two ways to increase the power of a test. These are going to require some
reading…Start with the second bullet on p. 487, then read the top of p. 488.
Record the two ways to reduce power
below.
Part 2: Chapter 21
Vocab Quiz! Name:____________________________
Use your textbook,
notes, and glossaries (ch. 19, 20,21) to complete the vocab quiz below!
1.) Fill in the blank with the appropriate word: When the p-value falls below the alpha
level, we say that our test is ____________ at that alpha level.
a. Significance Level
c. Statistically Significant
e. Not Statistically Significant
b. ___% Confident
d. A critical value
2.) Alpha Level/Significance Level
a. The
z* in the margin of error or confidence interval formula
b. The
“cutoff” value that we use to determine if we made a Type 1 or Type 2 error
c. The “cutoff” value that we use
to determine if we reject or fail to reject the null hypothesis
d. The level of confidence we have
for a given interval
e. The number of standard deviations/standard
errors from the mean for a given confidence level
3.) Alpha Level/Significance Level
a. The
probability of a type 2 error
b. The
probability of a type 1 error
c. The
likeliness that we correctly reject a false null hypothesis
d. The
power of a test
e. The
same as the confidence level for a given test
4.) The number of standard errors to move away from the mean
of a sampling distribution for a specified confidence level.
a. Sampling Error
b. Standard Deviation
c. Standard Error
d. Margin of Error
e. Critical Value
5.) A z or t score; measures the distance from the mean in
standard deviations
a. Confidence Interval
b.
Standardized Test Statistic
c. Alpha Level
d.
P-Valud
e. Confidence Level
6.) The probability of a type 2 error is:
a.
Alpha b. Beta c. Mu d. Sigma e.
The same as the confidence level
7.) This is our conclusion if the calculated p-value is
above the given level of significance:
a. Accept the null hypothesis
c. Reject the null hypothesis
e. Prove the null hypothesis is
true
b. Fail to reject the null
hypothesis
d. Fail to reject the alternative
hypothesis
8.) Type I Error
a. This
is when we mistakenly reject a true alternative hypothesis
b. This
is when we mistakenly fail to reject a true alternative hypothesis
c. This
is when we mistakenly reject a true null hypothesis
d. This
is when we mistakenly fail to reject a false null hypothesis
e. This
is when we mistakenly a true null hypothesis
9.) Type 2 Error
a. This is when we mistakenly
reject a true alternative hypothesis
b. This
is when we mistakenly fail to reject a true alternative hypothesis
c. This
is when we mistakenly reject a true null hypothesis
d. This
is when we mistakenly fail to reject a false null hypothesis
e. This
is when we mistakenly fail to reject a true null hypothesis
10.) Power
a. A
test’s ability to correctly accept a true null hypothesis
b. A
test’s ability to correctly prove a true null hypothesis
c. A
test’s ability to correctly fail to reject a true null hypothesis
d. A
test’s ability to correctly reject a false null hypothesis
e. A
test’s ability to correctly fail to reject a false null hypothesis
11.) If we had a p-value of 0.001, we would make this
decision (for any of the common alpha levels):
a. Accept the null hypothesis b. Reject
the null hypothesis
c. Prove the null hypothesis is
true d. Fail to
reject the null hypothesis
e. Fail to reject the alternative hypothesis
