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STUDY QUESTIONS FOR TEST 2
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Page 1
Chapter Seven
Closed Book Information:
1. What is the most important role of a hypothesis is to reflect the general problem
statement or question that was the motivation for asking the research question in
the first place.
2. What is a population? – The large group to whom the research might apply.
3. What is a sample? The elements of that larger group from whom the questions are
asked.
4. What is sampling error? The differences between the values of the sample and the
population parameter.
5. When samples are collected from populations, what is the goal? randomness
6. What is the null hypothesis? The time when the questions answer is ALWAYS NO –
no difference, no way, no how.
7. What is the research hypothesis? The research is a definite statement that there is a
relationship between variables. What is the purpose of the research hypothesis? It
directs the research questions.
8. The null hypothesis always refers to the population (sample/population). The
research hypothesis always refers to the sample (sample/population).
Open Book Information:
1. Given an example of a hypothesis, be able to:
a. Identify whether it is a research hypothesis or a null hypothesis
b. Identify whether a research hypothesis is directional or nondirectional
c. Write an equation to represent the hypothesis and be able to explain what
each symbol in the equation means
STUDY QUESTIONS FOR TEST 2
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Chapter Eight
Closed Book Information:
1. The study of probability is the basis for the normal curve and the foundation of
inferential statistics. The normal curve provides us with a basis for understanding
the probability associated with any possible outcome.
2. The tools of probability and the study of the normal curve allow a researcher to
determine the mathematical likelihood that a difference found between two
research outcomes is not due to CHANCE.
3. Be able to identify the three characteristics that are associated with the normal
curve.
a. Mean, median and mode are exactly the same
b. Perfectly symmetrical about the mean
c. Asymptotic – tails of the curve come closer and closer to the horizontal axis
but NEVER TOUCH!
2. Be able to identify the relative probability events that occur at various standard
deviations of the normal curve. 0.13%, 2.15%, 13.59%, 34.13% is 3 Sds, 2SDs, 1SDs
and above respectively
3. In a normal distribution almost 100% of all scores occur between -3 standard
deviations and +3 standard deviations.
4. Standard scores (such as z scores) allow researchers to do something that they
cannot do with raw scores? What is that? Compare data of differing disctributions.
5. Standard scores are comparable because they are standardized in units of
Standardized Deviations.
6. Z scores that are below the mean are negative and z scores that are above the
mean are positive.
7. Positive z scores always fall to the right of the mean and are in the upper half of
the distribution. Negative z scores always fall to the left of the mean and are in the
bottom half of the distribution.
8. A z score is simply the number of standard deviations from the mean.
9. When raw scores are represented as standard scores such as z scores, they are
comparable.
10. In hypothesis testing, if an event (score, outcome) seems to occur only 5 times (or
less) out of 100, (_5%), we will deem that event to be rather unlikely relative to all
other events that could occur.
11. Applying the concept in #12 to research, we know that if you are comparing two
outcomes in a research study (e.g., traditional approach to teaching reading vs.
new method to teaching reading) and the new reading approach yields a higher
score than the traditional approach at a probability level of .05 or less, we can
assume that the higher scores are not due to chance.
STUDY QUESTIONS FOR TEST 2
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Chapter Eight
Open Book Information:
1. Given a picture of the normal curve, be able to
a. Write in a rounded percentage figure for each area of the distribution
between standard deviations
b. Identify where the mean is located
c. Identify the approximate percentile rank for each standard deviation
2. Given a set of raw scores, be able to convert the scores to z scores.
3. Using Table B.1 in the appendix of your text and raw scores that you have
converted to z scores, be able to determine the probability of a score falling
a. above or below a particular score.
b. between two particular scores
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Chapter Nine Study Guide
Closed Book Questions:
12. Be able to recognize the definition of:
a. Significant difference
b. Significance level
c. Statistical significance
13. What is the largest probability value (p-value) that is typically accepted as having
statistical significance?
14. What does a p-value (significance level) of <.05 mean? <.01?
15. How is the p-value (significance level) related to the null hypothesis?
16. How is the p-value (significance level) related to the research hypothesis?
17. Researchers are typically hoping for a significance level that is in the range of
_____ to _____.
18. If you see a p-value that is stated as p>.05, the outcome is usually considered to
be _____________ .
a. This means that the odds of _________ a null hypothesis that is ________
exceeds 5%.
b. It also means that the probability of rejecting a null hypothesis that is true
can fall anywhere in a range from _______ to ________.
19. Be able to identify the meaning of:
a. Inferential statistics
b. The obtained value or test statistic value
c. The critical value of the test statistic
20. When looking at a picture of a normal distribution, know where on the distribution
you would want your obtained value (test statistic value) to fall.
21. Know a method for decreasing the likelihood of making a Type II error (i.e. accept
a false null hypothesis.
Closed Book Questions:
Given a scenario of a research project, be able to use the chart on page 159 to
identify:
4. Type 1 error
5. Type 2 error
6. An appropriate acceptance of the null hypothesis
7. An appropriate rejection of the null hypothesis
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Chapter 10 Study Guide
Closed Book Test
1. What does the term “independent samples” mean?
a) The two groups are not related to each other in any way
1.
2.
3.
4.
b) There is no overlap between the two samples (i.e., one cannot be a
member of both groups)
What is a t test for independent means?
a) A comparison of the means of two independent samples to determine if
they are statistically significant (i.e., that the difference in scores between
the two groups is due to group membership [research hypothesis] and not
due to something else, such as chance)
When doing a t test for independent means, what kinds of variables are you
using?
a) One must be a categorical or nominal variable, i.e., the way in which the
subjects are being separated into categories/groups
b) The other must be a continuous variable (i.e., measured on an interval or
ratio scale)
What are we trying to measure in an independent samples t test?
a) We are trying to determine whether the mean (average) scores on the
dependent variable differ according to which group one belongs to (the
independent variable)
b) Examples
 Does the average height (weight, length of life, etc.) of people depend
on being a man or a woman?
 Does the ability to perform an abstract mathematical problem depend
on the grade level of a student (e.g., 10th graders vs. 12th graders)?
How often are students being tested in an independent samples t test?
a) Only once
Remember: two different groups—in a classroom setting, you might use two
different classrooms and compare them on a particular test or assessment.
Presumably you would have done something different with each group and you
are comparing to see if your different strategy in one group made a difference.
Open Book Test
1. What are the steps to completing an independent samples t test?
a) Determine your null and research hypothesis
 The critical aspect of establishing the research hypothesis is that you must
decide if you are doing a one-tailed or two-tailed test
 A one-tailed test will be used if you are anticipating that one group will
perform at a higher level than the other group,
 A two-tailed test will be used if you are simply exploring to see if there is a
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difference between the groups, but you have no idea which group
might be higher. but you don’t know which one will perform higher
a) Set your level of significance (Type 1 error or the percentage of risk you will
take that the two means might actually be equal) What did we learn in the
last chapter that is the usual level of signifcance? (.05)
b) Select the test statistic (use the flow chart on page 173, but in this case we
know we are suing the independent samples t test)
c) Compute the test statistic value, also called the obtained value, in this case
referred to as the t value. (Although it is somewhat limiting in its scope, we
will stick with Hyperstat Online to do the calculations.)
 To do this, you should:
 Set up your groups and their accompanying scores. The example
below shows how I would set up the data for question #1 at the end
of the chapter. Go to the end of the chapter and look at the question.
In this data, I have used 1 to represent the boys and 2 to represent
girls. The second variable accounts for the number of times that the
student put his/her hand up.
Note that I had to set up the categorical variable using a number to represent the
categorical variables. In this case, the one represents boys and the 2 represents girls.
Gender Handup
1
9
2
3
2
5
2
1
1
8
1
4
2
2
2
6
1
9
1
3
2
4
1
8
2
3
1
10
2
6
1
8
2
7
1
9
2
9
1
8
2
7
2
3
2
7
STUDY QUESTIONS FOR TEST 2
2
1
1
1
1
2
2
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6
10
7
6
12
8
8
After you have entered the data into the Hyperstat Lab Analysis Tool,
select the variables. This time we will be selecting the grouping
variable instead of the predictor variable. This is because we have
two independent groups we are analyzing. The “handup” variable is
the dependent variable because we are testing to see if it varies by
group.
 You will now see that the Analysis Lab offers “independent groups t
test and confidence interval for ‘handup’” under the section entitled ttest/conf interval. Click on this.
 You now have the data needed to evaluate the significance of the
difference between your two group means. The following information
is currently pertinent:
 Mean 1 = the mean of the group of boys
 Mean 2 = the mean of the group of girls
 Mean 1 – Mean 2 = the difference between the two means
 t the t statistic (or t value) that is obtained once it is calculated
using the formula on page 176
 df = the degrees of freedom that are used on Table B.2 (n1 + n2 –
2) (see pages 333-334)
 p = the probability level (p-value) at which you are likely to be
making a Type 1 error (that is rejecting a null hypothesis when it is
really true)
 95% confidence interval—don’t worry about this term for now
d) The rest of the steps described in your textbook (steps 5-8 on pages 176 –
178) have already been done for you by the computer. Here are some
important things for you to remember, though:
 The degrees of freedom are determined by adding together the total
number of subjects in each group and subtracting 2 (1 for each group)
 Even if you don’t have a computer program giving you the exact pvalue, you can use the t-test table on pages 333-334 to determine if you
are above or below your established significance level.
 The t-test table on pages 333-334 is navigated by looking for the degrees
of freedom; sometimes you will have to choose whether to go higher or
lower if your exact number of degrees of freedom are not present.
 You will also have to determine if you are doing a one-tailed or twotailed test to decide which side of the chart to look at.

STUDY QUESTIONS FOR TEST 2

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Compare your established t value to the t values on the correct side of
the chart to determine whether you have met your established
significance level. In the example given, you will find that the t value of
3.0058 is not only significant at the p< 0.05 level but also significant at the
p<0.01 level. This explains why the actual calculated value is p=0.0055
on the Hyperstat Analysis Lab.
Data for Question 3 (look at this at the end of the chapter)
Inhome = 1 Out of home = 2
Group
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
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Anxiety
3
4
1
1
1
3
3
6
5
1
4
5
4
4
3
6
7
7
7
8
7
6
7
8
7
6
5
6
4
STUDY QUESTIONS FOR TEST 2
2
2
2
2
2
2
2
2
2
2
2
2
5
4
3
6
7
5
4
3
8
7
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STUDY QUESTIONS FOR TEST 2
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Chapter 11 Study Guide
Closed Book Questions
2. What does “dependent” mean in the term t-test for dependent means?
a) One group of subjects is being studied under different conditions, therefore
the variables are dependent, i.e. related to each other by the fact that they
are both the results of one subject
3. If you wanted to compare students using a pre- or posttest, what type of statistical
test would you typically use?
a) A t-test for dependent means
b) See information below for a different approach
4. What is the difference between a test of independent means and a test of
dependent means? When is each appropriate?
a) A test of independent means is used when you have two groups and each
one is tested only once on the same measure
b) A test of dependent means is used when you have one group that is being
tested under different conditions (such as pre- and post-test)
Closed Book Questions
5. Given a scenario describing a study that is to be undertaken, be able to use the
chart on page 190 to choose the correct statistical test. Examples:
a) Your school district has implemented a new intervention for helping students
pass the math section of the OGT. In order to see if there is any effect from
the intervention, a group of students who had taken the test in the Fall but
did not pass are selected to receive the intervention. They retake the OGT
in the Spring. Their scores from the first and second administration of the test
are compared. What kind of statistical test would you use to identify
whether there is a statistical difference from the first administration to the
second administration of the test?
 You would use the t-test for dependent means
6. SPSS does not allow you to do a one-tailed t-test for dependent means because it
always subtracts the second variable from the first variable (a problem with preand post-tests). If given the results of the SPSS test, what can you do to identify
the significance of the outcome?
a) Go to Table B.2 in Appendix B. Identify the degrees of freedom and the
level of significance required (usually .05) for a one-tailed test. Compare
the obtained statistic with the critical value required.
7. What is another way to obtain the exact significance level for a t-test for
dependent means?
a) A test called repeated measures analysis of variance (repeated measures
ANOVA) is virtually the same test as the t-test for dependent means. The
“repeated measures” indicate two scores for a single group on a single
measure.
b) This test can be done in Hyperstat. Do the following steps: (Use the sample
STUDY QUESTIONS FOR TEST 2
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data from Question #4 – see below)
 Enter/edit data
 Choose one variable as the dependent variable and the other variable
as the predictor variable (makes sense to use the pretest as the
predictor)
 Click on ANOVA/Advanced (the Advanced part will be available for
clicking)
 A window will come up that says “Choosing Variables for ANOVA.”
Choose both variables.
 Then click the button that says “Do ANOVA”
 The results will give you the typical results for ANOVA statistics (sum of
squares and mean square), but will also give you a p-value. This,
however, is what you need to know to see if you have obtained
statistically significant results.
 Remember that you can always obtain descriptive statistics, such as the
mean, by clicking on the descriptive statistics area.
8. Let’s test some to determine that the results are the same:
Question #4:
Before_treat
45
46
46
44
32
47
34
42
33
45
21
32
23
36
41
43
27
24
38
41
41
38
47
31
41
22
32
36
22
36
34
27
36
41
19
44
23
32
22
32
Question #5:
After_treat
STUDY QUESTIONS FOR TEST 2
Before
1.3
2.5
2.3
8.1
5
7
7.5
5.2
4.4
7.6
9
7.6
4.5
1.1
5.6
6.2
7
6.9
5.6
5.2
After
6.5
8.7
9.8
10.2
7.9
6.5
8.7
7.9
8.7
9.1
8.4
6.4
7.2
5.8
6.9
5.9
7.6
7.8
7.3
4.6
Question # 6:
Nibbles
9
3
1
6
5
7
8
3
10
3
5
2
9
6
2
5
8
1
6
Wribbles
4
7
6
8
7
7
8
6
7
8
9
8
7
3
6
7
6
5
5
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STUDY QUESTIONS FOR TEST 2
3
6
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Chapter 12—Study Guide
Closed Book Questions:
8. Analysis of variance (ANOVA) is used as a test of statistical significance
when_______________.
a. More than one group is being compared on one measure.
9. The test statistic for ANOVA is the _______ test.
a. F
10. When there is only on grouping dimension, the type of ANOVA is referred to as
____________________________.
a. One-way ANOVA or simple ANOVA
11. The technique behind ANOVA is that it compares the variance that is due to
differences in individuals _________ groups to the variance that is due to the
differences __________ groups.
a. Within
b. Between
12. Know the purpose of a post hoc comparison, such as Bonferroni’s.
a. To allow you to see which means within an ANOVA are actually different
from each other
Open Book Questions:
2. Given a scenario that requires a simple ANOVA, be able to:
a. Write a null hypothesis
i. There is no difference in the means for the 3 (or 4 or 5, etc.) groups
b. Write a research hypothesis
i. There is an overall difference in the means of the 3 (or 4 or 5, etc.)
groups
c. Be able to calculate the statistic using Hyperstat (see below)
d. Be able to interpret what the statistical output tells you about statistical
significance
e. Be able to look at the output of a post hoc comparison like Bonferroni’s and
say which means are actually different from each other.
i. See page 216. In the first column, each group is compared with each
other group (5 hours with 10 hours and five hours with 20 hours, etc.)
ii. Look across the row to find the significance level of each comparison.
If it is less than .05, you can determine that the differences in means
are not due to chance.
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Hyperstat Directions:
9. List your scores in two columns; one should be the grouping variable and the other
should be some type of score.
10. Select the “score” as the dependent variable.
11. Select the grouping variable in the drop down menu that is called “grouping
variable.”
12. Click on ANOVA and you will have the necessary statistics to interpret your
findings.
Example from book:
Group
1
87
1
86
1
76
1
56
1
78
1
98
1
77
1
66
1
75
1
67
2
87
2
85
2
99
2
85
2
79
2
81
2
82
2
78
2
85
2
91
3
89
3
91
3
96
3
87
3
89
3
90
3
89
3
96
3
96
3
93
Score
Question #3—Data Set 2
STUDY QUESTIONS FOR TEST 2
Practice
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
2
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
Time
58.7
55.3
61.8
49.5
64.5
61
65.7
51.4
53.6
59
64.4
55.8
58.7
54.7
52.7
67.8
61.6
58.7
54.6
51.5
54.7
61.4
56.9
68
65.9
54.7
53.6
58.7
58.7
65.7
66.5
56.7
55.4
51.5
54.8
57.2
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STUDY QUESTIONS FOR TEST 2
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Chapter 14—Study Guide
Closed Book Section
1. What test is used when trying to identify the significance of a correlation?
a) T-test for the significance of a correlation coefficient
1. This is a review. When calculating the t-test for the significance of a correlation
coefficient, a one-tailed test indicates that the researcher is willing to predict the
___________ (direction) of the correlation. A _________ __________ (two-tailed test)
indicates that the researcher is not willing to predict the direction of the
correlation.
2. What is the test statistic for the correlation?
a) The correlation coefficient itself
3. True or False? A strong significant correlation indicates that one variable causes
the other. Explain your answer.
a) False
b) Correlation never can be interpreted as cause-effect. It simply determines
a relationship. Other variables may be the source of the relationship (e.g.,
the spurious correlations we discussed earlier, such as the seeming
relationship between ice cream and crime rates in summer.)
Open Book Section
4. Be able to do the following:
a) Write a null hypothesis for a correlation coefficient
 E.g., There is no relationship between variable A and variable B
b) Write a research hypothesis for a correlation coefficient
 One-tailed research hypothesis:
 There is a direct (positive) relationship between variable A and
variable B, or
 There is an indirect (negative) relationship between variable A and
variable B
 Two-tailed research hypothesis
 There is a relationship between variable A and B that differs from the
value of 0.
c) Calculate a correlation coefficient
 Use Hyperstat to do this
d) Determine the degrees of freedom
 n—2, where n = the number of pairs used to compute the correlation
coefficient
e) Use Table B.4 to determine the probability that the null hypothesis is true
 Using the degrees of freedom, the type of test (one-tailed or two-tailed),
and the correlation coefficient, determine whether the obtained value is
greater than the critical value
 See Question 1 in Chapter 14 for examples
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Examples for practice (in Hyperstat):
Question #2
Motivation
1
6
2
7
5
4
3
1
8
6
5
6
5
5
6
6
7
7
2
9
8
8
7
6
9
7
8
7
8
9
GPA
3.4
3.4
2.5
3.1
2.8
2.6
2.1
1.6
3.1
2.6
3.2
3.1
3.2
2.7
2.8
2.6
2.5
2.8
1.8
3.7
3.1
2.5
2.4
2.1
4.0
3.9
3.1
3.3
3.0
2.0
Note: When you obtain the correlation statistics, you are given the significance level.
This would be for a two-tailed test. If you needed to test for a one-tailed, you can just
use the Chart B.4 in the appendix.
STUDY QUESTIONS FOR TEST 2
Question #4:
Age_months
12
6
15
8
9
4
7
5
18
14
24
18
15
7
16
6
21
12
15
17
Words_known
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