Part I: Concepts
These questions are based on the Nolan and Heinzen reading and endofchapter questions.
1. What are always the mean and standard deviation of the zdistribution?
2. Define the central limit theorem.
3. Fill in the blanks: A zscore is based on a distribution of
_____________, while a zstatistic is based on a distribution of
__________________.
4. Endofchapter problems: Remember to show work to receive partial
credit where applicable. For help working on these problems, refer to
the presentation from this module/week on the normal curve and computing
zscores.
· Raw and zscores: 6.16 and 6.20
· Estimating percentages under normal curve: 6.27
· Distribution of means and zstatistic: 6.28 and 6.30
Part II: SPSS Analysis
1. Green and Salkind, Lesson 21, Exercise 1
Open the “Lesson 21 Exercise File 1” document (found in the course’s
Assignment Instructions folder) in order to complete these exercises.
a. Create a histogram of the anxiety raw scores and paste it into your homework document.
b. Using the descriptives method covered in the presentation and
chapter, transform the anxiety raw scores to zscores, creating a new
variable called “z_anxiety.” Paste the output of descriptive statistics
in your homework document. These descriptive statistics should describe
the original raw scores and not the new z scores.
c. Remember that the mean of a standard normal distribution is z = 0
and the standard deviation is 1. What is the zscore that is closest to 0
(on either side of the mean) in your data set? What is the zscore that
is the farthest from 0 (on either side of the mean) in your data set?
d. Based on the histogram from (a) and the answers to (c), would you
describe the anxiety data as being normally distributed? Why or why not?
Support your answer with information from the chapter and presentations
regarding normal and standard normal zdistributions.
Part III: SPSS Data Entry and Analysis
1. The following data represent IQ scores of a sample of 30 high
school students. In the general population, IQ scores have a mean of 100
and a standard deviation of 15.
IQ Scores

123
119
104
145
108
100
115
105
60
122
105
87
98
124
80

93
89
123
118
104
112
96
85
98
105
91
113
82
124
90

a. Generate descriptive statistics and a histogram for this variable. Based on the data and graph, choose
1 measure of central tendency and 1 measure of dispersion (variability)
that best describes the data set. Justify why you chose these measures in a statement beneath the output.
b. In your data set, standardize the IQ scores by transforming them
into zscores under a new variable “ZIQ.” Using your data set as a
reference, what zscore corresponds to a raw IQ score of 115? To a raw
IQ score of 60? To a raw IQ score of 104?
c. Based on what you have been told about IQ scores in the beginning
of the problem, does this sample’s distribution seem to reflect the
distribution of IQ scores in the general population? Why or why not?
Part IV: Cumulative
1. (NonSPSS) A cognitive psychologist wants to find out whether
playing Minecraft® affects fourth graders’ scores on a visuospatial
task. He assigns 30 fourth graders to 1 of 2 groups. Group 1 plays
Minecraft® for 20 minutes, then completes the visuospatial task. Group 2
completes the visuospatial task without playing Minecraft®.
a. What is the independent variable in this experiment?
b. What is the dependent variable?
c. What is the likely null hypothesis for this experiment?
d. What is the likely research hypothesis for this experiment?
2. (NonSPSS) A clinical psychologist wants to test a new longterm
treatment program for people diagnosed with bipolar disorder. She
assigns 20 participants to the new treatment program and 20 participants
to a standard treatment program.
a. State the likely null hypothesis for this study.
b. State the likely research hypothesis for this study.
3. (SPSS) A criminal psychologist wants to examine the level of
narcissistic personality traits between those who are diagnosed with
antisocial personality disorder (ASPD) and those who do not qualify for
ASPD. She administers a measure of narcissistic personality traits where
higher scores indicate higher levels of narcissism and scores range
from 0–35.
ASPD Diagnosis

No ASPD Diagnosis

23
11
19
21
22
9
16
27
31
31

10
8
19
13
6
4
9
15
11
7

a. Create a new SPSS data file for these scores. Your file must have 2
variables: diagnosis and score. Your diagnosis variable must be set up
as a 1column grouping variable with 2 groups (diagnosis, no diagnosis)
coded numerically. This will be much like the gender variable you
created in a previous module/week. For example, if you code ASPD
Diagnosis as 1 and No ASPD Diagnosis as 2, then the SPSS file will
appear somewhat like the following:
Column 1

Column 2

“Diagnosis”

“Score”

1

23

1

11

1

19

All ASPD Diagnosis scores from the table above will appear in a similar fashion.
Then, enter No ASPD Diagnosis information as:
Continue in this fashion to the end of the file.
b. Compute descriptive statistics by diagnosis (that is, for each of
the two groups in one table) using similar steps to those covered in
Green and Salkind’s Lesson 21 and in the Module/Week 3 presentation (HS
GPA scores by Gender). Paste this into your homework document.
c. Construct a boxplot to show the difference between the mean scores of the 2 groups.