Discuss why analyzing data is important in the field of criminal justice. Explain your reasoning in detail. To write your Discuss post, follow the steps in this tutorial: https://bethelu.libguides.com/researchforclassUpload your discussion post tutorial worksheet to the Dropbox for credit by Wednesday at 11:59 pm CST. Respond to this question with a minimum of 250 words and two scholarly sources from the Library by Wednesday at 11:59 pm CST.
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HOW TO RESEARCH
FOR YOUR ESSAYS
SEARCH STRATEGY
1. What’s your topic?
2. What keyword synonyms will you search in the databases?
3. Which general resource(s) and which specific resource(s) will you use for your essay?
For example, a general resource is the World Encyclopedia of Police Forces and a
specific resource is American Journal of Criminal Justice from the EBSCO database.
PULL IT TOGETHER
1. Look through the articles you have and take notes on what the authors say.
2. How would you explain your argument to a coworker?
a. What’s your claim?
b. What’s your evidence?
c. Does any research disagree with your claim?
d. What’s your response to the objections?
GIVE CREDIT
1. Did you include an author’s idea in your paper?
For help, contact
[email protected]
615.277.8980
⃞ Yes
⃞ No
2. Did you paraphrase?
⃞ Check your paraphrase by comparing it to the original source. Is your
wording and sentence structure unique?
⃞ Did you include an in-text citation after your paraphrase?
3. Did you use the exact words from a sentence you read?
⃞ Did you put the exact words in quotation marks?
⃞ Is there an in-text citation with a page number in the sentence?
For help, contact
[email protected]
615.277.8980
© Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION.
Table of Contents
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© Jones & Bartlett Learning, LLC. NOT FOR SALE OR DISTRIBUTION.
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Copyright © 2013 by Jones & Bartlett Learning, LLC, an Ascend Learning
Company
All rights reserved. No part of the material protected by this copyright
may
be
reproduced or utilized in any form, elecL
tronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without
written permission from the copyright owner.
E
This publication is designed to provide accurate and authoritative information in regard to the Subject Matter covered.
It is sold with the understanding that the publisher is not engaged inS
rendering legal, accounting, or other professional
service. If legal advice or other expert assistance is required, the service of a competent professional person should
,
be sought.
Statistics in Criminology and Criminal Justice: Analysis and Interpretation, Fourth Edition is an independent publication and has not been authorized, sponsored, or otherwise approved by the owners of the trademarks or service marks
referenced in this product.
S
Some images in this book feature models. These models do not necessarily
endorse, represent, or participate in the
H
activities represented in the images.
A
Production Credits
Publisher: Cathleen Sether
N
Acquisitions Editor: Sean Connelly
Editorial Assistant: Caitlin Murphy
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Associate Production Editor: Rebekah Linga
Marketing Manager: Lindsay White
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Manufacturing and Inventory Control Supervisor: Amy Bacus
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Composition: Northeast Compositors, Inc.
Cover Design: Kristin E. Parker
Cover Image: © artida/ShutterStock, Inc.
Printing and Binding: Edwards Brothers Malloy
Cover Printing: Edwards Brothers Malloy
1
To order this product, use ISBN: 978-1-4496-8860-8
9
Library of Congress Cataloging-in-Publication Data
0
Walker, Jeffery T.
Statistics in criminology and criminal justice : analysis and interpretation
/ Jeffery T. Walker and Sean Maddan.
9
— 4th ed.
p. cm.
T
Includes bibliographical references and index.
ISBN 978-1-4496-1630-4 (pbk.) — ISBN 1-4496-1630-5 (pbk.) S
1. Criminal justice, Administration of–Statistical
methods. 2. Criminal statistics–Research. I. Maddan, Sean. II. Title.
HV7415.W32 2013
364.01’5195–dc23
2012015761
6048
Printed in the United States of America
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THEORY
METHODS
Observation
Primary Question
Research Questions
Null Hypothesis
M
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L
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S
,
Research Hypotheses
Research Design
Concepts
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H
A
Operationalization
N
N
Variables
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Gather Data
Draw Conclusions
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Statistical Analysis
9
T
S
Communicate Results
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Chapter 1
The Logic of Comparisons
and Analysis
Statistical thinking will one day be asMnecessary for efficient citizenship as
I
the ability to read and write.
Learning Objectives
L
E
S
,
—H. G. Wells
Understand the difference between statistics and math.
Explain the role of statistics in the process of scientific inquiry.
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■■ Discuss the relationship among theory, research methods, and statistics.
H
■■ Identify the steps in the research process.
■■ Understand the relationship among
Aprimary questions, research questions, null
hypotheses, and research hypotheses.
N
■■
■■
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Introduction: WhyOAnalyze Data?
Discovery and innovation may be the distinguishing
characteristics between modern
N
1-1
human activity and that of our ancestors. The Renaissance period brought forth an
emphasis on learning and advancing our way of doing things that has prevailed to the
present. Scientists, inventors, and others1involved in the process of scientific inquiry
have often been held in awe for their works.
9 Galileo, Einstein, Madam Curie, and others are singled out in grade school books for their works and discoveries. As you will
0
learn, so too should be people such as Pearson, Kendall, and Yule.
9 The process of scientific inquiry proStatistical analysis is all about discovery.
vides a method of examining things thatTinterest us in a systematic manner. This process generally requires evidence to support an argument. One of the clearest methods
S
of establishing evidence is by examining numbers associated with the objects being
studied. That examination takes place through statistical analysis. As such, statistical
analysis is the linchpin of discovery, and mastery of it draws us closer to Einstein and
Galileo.
3
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4 Chapter 1
1-2
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The Logic of Comparisons and Analysis
Some Statistical History
The earliest form of what is now considered statistical analysis was developed by
Pythagoras in the 6th century BC. This was the forerunner of descriptive statistics
(what would eventually be known as the mean, or what is commonly known as an
average). The other type of statistical analysis (inferential statistics) is thought to
have first developed in the Orient around 200 BC (Dudycha and Dudycha, 1972). This
was a form of probability analysis used in assessing whether an expected child was
likely to be male or female. Probability theory, as it would come to be known, continM
ued in the form of gambling mathematics in the works of Blaise Pascal (1623–1662)
I
and Lord Christianus Huygens (1629–1695) (David,
1962). Many of the other descriptive statistics were developed in the late 1800sLand early 1900s by mathematicians and
scientists such as Galton (1883) and Pearson (1895).
E
Statistics moved beyond gambling and purely mathematical concepts through
what was called political arithmetic, a term S
coined because of its close association
with those studying political topics, including
, economics. (This probably began the
close association between political lying and statistical lying.) The first known use
of this political arithmetic was by John Graunt (1662), who used what is now called
descriptive statistics to study London’s deathSrates. Although there is fierce debate
concerning the original use of the term statistics
H (Yule, 1905), the position with the
greatest support is that it was coined by Eberhard August Wilhelm von Zimmerman in
the preface of A Political Survey of the PresentAState of Europe (1787). Modern use of
Nis often attributed to R. A. Fisher and
the term statistics (as opposed to mathematics)
his work Statistical Methods for Research Workers
N (1925), wherein he stated that “a
statistic is a value calculated from an observed sample with a view to characterizing
the population from which it is drawn.” SinceO
that time, statisticians have added to the
techniques available to analyze data, many adding
N their names to the procedures; and
the addition of statistical techniques continues today. Analysis procedures have been
added to the statistical repertoire in the past few years that have greatly increased the
1 and other fields to examine the relaability of researchers in sociology, criminology,
tionship between variables more accurately. 9
0 is a statistic.
A single death is a tragedy, a million deaths
1-3
Uses of Statistics
9
T
S
—Joseph Stalin
The term statistics is often misunderstood because there are actually two practical
applications of it. The first, reflecting the history of the term, is a collection of data—
often expressed in summary form—that is collected and preserved. The best example
of these are census statistics or mortality statistics, which depict the characteristics of
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1-4 Theory Construction at a Glance
5
the living or the causes of death, respectively. The second application is the subject of
this text: a method of analyzing data.
Statistics as you will come to know them are methods used to examine data collected in the process of scientific inquiry. These methods allow researchers to think
logically about the data and to do one of two things: to come to some succinct and
meaningful conclusions about the data (descriptive statistics), or to determine—or
infer—characteristics of large groups based on the data collected on small parts (samples) of the group (inferential statistics). For example, data could be gathered on all
correctional officers in Arkansas for a research
M project to determine the sex and race
breakdown of the officers. This would be a descriptive analysis that could be used to
I Arkansas Department of Correction. Alterexamine the employment patterns for the
L from each state could be collected and the
natively, a sample of correctional officers
data from the sample used to make statements
about all correctional officers in the
E
nation. This would be drawing conclusions (inferences) about a large group based on
information about a sample of the group.S
Statistical analysis is the workhorse of
, discovery and knowledge. The scientific process, using research to test theory, requires that empirical evidence (data) drawn from
the research subjects be examined systematically. The use of mathematics in general
and statistical analysis in particular allowsSresearchers to make these comparisons and to
discover new information that will provide
Ha better understanding of their subject.
In the scientific process, the purpose is usually to discover something that was
A
previously unknown or to prove something true or false that was previously thought to
be true but was never supported by hardN
evidence. The way to obtain that evidence is
by gathering information (data) and subjecting
N it to statistical analysis.
1-4
O
Theory Construction
N at a Glance
Three elements in social science research, or any research for that matter, are essential
to sound investigation: theory, research1methods, and statistical analysis. Although
these elements are intimately linked, there is debate—even among those most sup9 ordering, importance, and what should be
portive of the research process—on their
included from each element in a textbook.
0 It is not possible to cover all of these elements adequately in one course or in one textbook, so it becomes an issue of how
9
much of each element should be included in a discussion of the other. In this book,
T research spans this chapter and several that
theory is covered primarily in this chapter,
follow, and statistical analysis prevails thereafter.
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What Is Theory?
At the most basic level, theory consists of statements concerning the relationship or
association among social phenomena such as events and characteristics of people or
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6 Chapter 1
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The Logic of Comparisons and Analysis
things. For example, in criminology, there are theories addressing how people learn
to be criminal. In these theories, statements are constructed dealing with the role of
peers in a person’s learning criminal behavior, how the rewards from a crime can influence behavior, and what influence punishment can have on the decision to commit a
crime.
The goal of these statements is to develop explanations of why things are as they
appear and to try to explain their meaning. From an early age, humans have ideas
about the causes of events and why things work the way that they do. The problem
with these explanations, however, is that they
Mare often too simplistic to be of any
real value. Theory attempts to provide a stronger foundation for these ideas by asking
I
questions about them, such as:
■■
What is the point of all of this?
■■
What does it mean?
Why are things this way?
■■
L
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,
conjecture
Without theory, there is often only
and war stories. With theory, we
may begin to develop statements or ideas that are based on sound observation and
thought.
S
H
Theory and Research
Theory may be developed in several ways. Researchers
may look at the world around
A
them, find the social phenomena that pique their interest, and begin to develop stateN
ments concerning why these phenomena work the way they do. This is called inducN crime trends in a city for a number
tion. An example could be a researcher who follows
of years. She may begin to see that the crimesOfollow a definite pattern of movement
in the city, moving from east to west across the city. From this, she might set out to
N
determine what the cause of this movement could be, ultimately developing a theory
of crime movement in urban areas. This is a process of moving from data to theory and
attempting to make sense of the data with the 1
theory.
Alternatively, researchers may become curious about something and set out to
9
develop statements and then to test them. This is called deduction. The process of
deduction begins with an idea and an attempt to0test the idea with data and analysis. For
example, a researcher might believe that increased
9 supervision of probationers would
prevent them from becoming involved in subsequent crimes. This researcher might
T
create an experiment where a random sample of probationers are put under intensive
S a normal amount of supervision.
supervision while another random sample receives
The results of this experiment could either support or refute the researcher’s initial
beliefs. This is a process of moving from theory to data, where the data tests the theory.
It should be noted that Sherlock Holmes was not exactly correct in his understanding
of the difference between induction and deduction. When Holmes made his famous
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1-5 The Process of Scientific Inquiry
7
statement, “brilliant deduction, Watson!”, he should actually have been commending
Watson on his inductive reasoning. Watson was drawing conclusions based on what he
had observed, not testing previously developed conclusions.
Finally, and probably most often the case, a researcher may start with either induction or deduction, but by the time a project is finished, he or she has used both induction
and deduction. This is called retroduction. With this process, the researcher investigating supervision of probationers might conduct the intensive supervision experiment as a
deductive process. After examining the data, however, it might be obvious that the experiment could be done better or that there was
M something in the data that needed further
explanation. For example, those probationers who received the most supervision were
I
successful, whereas those who received intensive,
but less than the most intensive, supervision were not successful. The researcherL
might then rethink part of the theory and set out
to retest it. This process might continue until
E the theory was supported or disproven. This
is a process of moving from theory to data to theory and so on; or data to theory to data and
S process between induction and deduction.
so on. The key here is that it is an alternating
,
1-5
The Process of Scientific Inquiry
S
The process of scientific inquiry (using a deductive method) is shown in Figure 1-1.
As shown in this diagram, theory is atH
the starting point of the process. Theory is
driven by observations and leads researchers
A to initiate the research process through
primary questions and research questions. It is from this process of theory building
that researchers follow the process fromNdeveloping a null hypothesis to communicating results. The process of scientific N
inquiry and its individual parts are discussed
further in the remainder of the chapter. O
Observation and Inquisitiveness N
The first steps in the process of scientific inquiry, and among the most important, are
often overlooked: observation and inquisitiveness.
Many research projects are never
1
begun because the researcher was not aware of his or her surroundings or did not rec9
ognize something as a topic worthy of research.
It is often theory that stimulates observation
and scientific inquiry. As you go
0
through school and read research and material you find interesting, you will sometimes
9
think that you have a better way to do something, or what you read may stimulate you
T process to evaluate your observations
in other areas. By using a structured scientific
and formulate statements of why these phenomena
are behaving the way they are, you
S
are developing theory.
An example of inductive theory development can be shown in Robert Burgess’s
Zonal Hypothesis. Students at the University of Chicago were making maps of Chicago showing different characteristics of neighborhoods, such as welfare, infant
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8 Chapter 1
n
The Logic of Comparisons and Analysis
THEORY
METHODS
Observation
Primary Question
Research Questions
Null Hypothesis
M
I
L
E
S
Concepts
,
Research Hypotheses
Research Design
S
H
A
Variables
N
N
O
Gather Data
N
Operationalization
Statistical Analysis
Draw Conclusions
Communicate Results
1
9
0
9
T
S
Figure 1-1 Process of Scientific Inquiry: Theory, Research Methods, and Statistical
Analysis
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1-5 The Process of Scientific Inquiry
9
ortality, and housing. Burgess observed that these maps followed very similar patm
terns throughout the city. His observations led him to develop a theory about how
cities grow and change. The theory he developed from these maps proposed that cities
grow in rings similar to when a rock is thrown into the water. In this configuration,
the …
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