Statistics in Criminal Justice : Analysis and Interpretation,9780834210868

Statistics in Criminal Justice : Analysis and Interpretation

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ISBN13: 9780834210868
ISBN10: 083421086X
Format: Hardcover
Pub. Date: 1999-08-01
Publisher(s): Jones & Bartlett Pub
List Price: $102.95

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Author Biography

Jeffery T. Walker, Ph.D. is a professor of criminal justice at the University of Arkansas at Little Rock.

Table of Contents

PART I---FUNDAMENTAL CONCEPTS OF STATISTICAL ANALYSIS
The Logic of Comparisons and Analysis
1(18)
Introduction: Why Analyze Data?
1(1)
Some Statistical History
1(1)
Uses of Statistics
2(1)
Theory Construction at a Glance
2(4)
What Is Theory?
3(1)
Theory and Research
3(2)
Observation and Inquisitiveness
5(1)
Primary Questions
5(1)
Research Questions
5(1)
Research: Movement from Theory to Data and Back
6(4)
Formulating Hypotheses
6(1)
Constructing the Research Design
7(1)
Developing Concepts
7(1)
Operationalizing
8(1)
Gathering the Data
9(1)
Statistical Analysis: The Art of Making Sound Comparisons
10(3)
Foundations of Valid Comparisons
11(1)
Comparing Appropriate Phenomena
11(1)
Using Comparable Measures
11(1)
Choosing Analysis Methods That Best Summarize the Data
12(1)
Drawing Conclusions
12(1)
Communicating the Results
12(1)
Data and Purposes of This Book
13(6)
Variables and Measurement
19(24)
The Variable Defined
19(1)
Transforming Characteristics into Data: The Process of Measurement
19(2)
How Variables Can Differ
21(13)
Levels of Measurement
21(1)
Nominal
22(1)
Ordinal
23(1)
Interval
24(3)
Ratio
27(1)
The Process for Determining Level of Measurement
28(1)
Changing Levels
29(1)
Scale Continuity
30(1)
Use in the Research Process
31(1)
Dependent Variable
31(1)
Independent Variable
31(1)
Confounding Variable
32(2)
Conclusion
34(9)
PART II---UNIVARIATE STATISTICS
Not All Statistical Analyses Involve Numbers: Summarizing Data through Graphical Representation
43(30)
Introduction
43(1)
Frequency Distributions: A Chart of a Different Color
44(6)
Conventions for Building Distributions
45(1)
Frequency Distributions
46(1)
Frequency Distributions for Grouped Data
47(1)
Percentage Distributions
48(2)
Combination Distributions
50(1)
Graphical Representation of Frequencies
50(7)
Pie Charts
51(1)
Histograms and Bar Charts
52(2)
Polygons and Area Charts
54(3)
Analyzing Univariate Statistics
57(1)
Analyzing Change
58(2)
Line Charts
58(1)
Ogives
59(1)
Analyzing Bivariate and Multivariate Data
60(4)
Scatter Plots
60(1)
Normal Probability or P-P Plots
61(2)
Path Diagrams
63(1)
Analyzing Geographic Distributions
64(5)
Pin, Spot, or Point Maps
64(1)
Choropleth Maps
64(2)
Constructing Effective Choropleth Maps
66(1)
Problems With Choropleth Maps
66(3)
Conclusion
69(4)
Measures of Central Tendency
73(20)
Measures of Central Tendency
73(13)
Mode
74(4)
Median
78(1)
Median for Ungrouped Data
79(1)
Median for Grouped Data
79(4)
Mean
83(2)
Selecting the Most Appropriate Measure of Central Tendency
85(1)
Conclusion
86(7)
Measures of Dispersion
93(18)
Introduction
93(1)
Deviation and Dispersion
93(1)
Measures of Dispersion
94(10)
Range
95(1)
Index of Dispersion
96(3)
Mean Absolute Deviation
99(1)
Variance
100(3)
Standard Deviation
103(1)
What Use Do I Have for the Variance and Standard Deviation?
104(1)
Selecting the Most Appropriate Measure of Dispersion
104(1)
Conclusion
105(6)
The Form of a Distribution
111(16)
Introduction
111(1)
Moments of a Distribution
111(1)
Number of Modes
111(1)
Skewness
112(3)
Analysis of Skew
113(2)
Kurtosis
115(1)
Analysis of Kurtosis
115(1)
The Importance of Skewness and Kurtosis
115(1)
Design of the Normal Curve
116(5)
Points to Remember About the Normal Curve
121(1)
Conclusion
121(6)
PART III---BIVATIATE STATISTICS
Introduction To Bivariate Descriptive Statistics
127(12)
Introduction
127(1)
Bivariate Tables and Analysis
128(2)
Statistical Tables versus Presentation Tables
128(2)
Constructing Bivariate Tables
130(4)
Ordinal Level Table Construction
131(2)
Statistical Tables
133(1)
Nominal Level Table Construction
134(1)
Analysis of Bivariate Tables
134(1)
Conclusion
135(4)
Measures of Existence/Statistical Significance of a Relationship
139(24)
Nominal Level Measures of Existence
139(1)
Tables, Percentages, and Differences
139(4)
Chi-square
143(9)
Requirements for Using Chi-square
149(2)
Limitations of Chi-square
151(1)
A Final Note on Chi-square
152(1)
Tests of Existence for Ordinal and Interval Level Data
152(4)
Calculation and Interpretation for Ordinal Data
152(1)
Spearman's Rho and Pearson's r
153(3)
An Issue Of Significance
156(1)
Conclusion
156(7)
Measures of the Strength of a Relationship
163(34)
What Is Association?
164(1)
Nominal Level Data
164(5)
Calculation
166(1)
Interpretation
167(2)
Ordinal Level Data
169(14)
Tau
170(1)
Calculation
170(4)
Interpretation
174(3)
Gamma
177(1)
Calculation
177(1)
Interpretation
178(1)
Somers'd
179(1)
Calculation
179(1)
Interpretation
180(1)
Spearman's Rho
181(1)
Calculation
181(1)
Interpretation
182(1)
Limitations
183(1)
Interval Level Data
183(8)
Pearson's r
185(2)
Calculation
187(1)
Correlation Matrixes
188(1)
Interpretation
188(1)
Coefficient of Determination
189(1)
Correlation and Causation
189(2)
Limitations
191(1)
Conclusion: Selecting the Most Appropriate Measure of Strength
191(6)
Measures of Direction and Nature of a Relationship
197(16)
Direction of the Association
197(4)
Establishing Direction for Ordinal Level Data
197(3)
Establishing Direction for Interval/Ratio Level Data
200(1)
Nature of the Association
201(3)
Establishing the Nature of the Distribution for Nominal and Ordinal Level Data
201(1)
Establishing the Nature of the Distribution for Interval/Ratio Level Data
202(2)
Conclusion
204(9)
PART IV---MULTIVARIATE STATISTICS: BRIDGING THE GAP BETWEEN DESCRIPTIVE AND INFERENTIAL STATISTICS
Introduction to Multivariate Statistics
213(12)
Introduction: When Two Variables Just Aren't Enough
213(1)
Interaction Among Variables
213(3)
Causation
216(3)
Association
216(1)
Temporal Ordering
216(2)
Elimination of Rival Factors and Relationships
218(1)
Other Issues for Multivariate Analysis
219(2)
Robustness
219(1)
Error
220(1)
Parsimony
221(1)
Conclusion
221(4)
Multivariate Measures of Association
225(30)
Introduction
225(1)
Regression
225(9)
Assumptions
226(2)
Analysis and Interpretation
228(5)
Limitations
233(1)
Factor Analysis
234(12)
Assumptions
235(1)
Analysis and Interpretation
236(1)
Univariate Analysis
236(1)
Preliminary Analyses
236(1)
Factor Extraction
237(4)
Factor Rotation
241(5)
Use of Factors in Other Analyses
246(1)
ANOVA
246(5)
Assumptions
247(1)
Analysis and Interpretation
248(3)
Conclusion
251(4)
PART V---INFERENTIAL STATISTICS
Introduction to Inferential Analysis
255(18)
Descriptive and Inferential Analyses
255(1)
Terminology and Assumptions
256(1)
The Normal Curve
257(1)
Probability
258(2)
Sampling
260(4)
Probability Sampling
261(1)
Simple Random Sampling
261(1)
Systematic Sampling
262(1)
Stratified Sampling
262(1)
Cluster or Multistage Sampling
262(1)
Nonprobability Sampling
263(1)
Purposive Sampling
263(1)
Quota Sampling
263(1)
Snowball Sampling
264(1)
Accidental/Convenience Sampling
264(1)
Sampling Distributions
264(2)
Central Limit Theorem
266(1)
Confidence Intervals
267(3)
Calculating Confidence Intervals
267(2)
Interpreting Confidence Intervals
269(1)
Conclusion
270(3)
Hypothesis Testing
273(14)
Introduction
273(1)
Null and Research Hypotheses
273(2)
Steps in Hypothesis Testing
275(4)
Developing the Research Hypothesis
275(1)
Developing the Null Hypothesis
275(1)
Drawing Samples
276(1)
Selecting the Test
276(1)
One-Tailed and Two-Tailed Tests
276(1)
The Obtained Value
277(1)
Significance and Critical Regions
277(1)
Making a Decision
278(1)
Type I and Type II Errors
279(2)
Which Is Better, a Type I or Type II Error?
281(1)
Power of Tests
281(2)
Conclusion
283(4)
Hypothesis Tests
287(22)
Introduction: Tests of Hypothesis
287(1)
Z-Test
287(7)
Calculation and Example
288(2)
Interpretation and Application: Known Probability of Error
290(3)
One-Sample versus Two-Sample Z-Tests
293(1)
t-Test
294(7)
Assumptions of a t-Test
295(1)
Calculation and Example
296(1)
SPSS Analysis for Z-Tests and t-Tests
297(1)
One-Sample t-Test
298(1)
Two-Sample t-Test
299(2)
F-Test
301(3)
Calculation and Example
301(2)
SPSS Output for an F-Test
303(1)
Chi-square Test for Independence
304(1)
Conclusion
305(4)
Putting It All Together
309(6)
Introduction
309(1)
The Relationship Between Statistics, Methodology, and Theory
309(1)
Describe It or Make Inferences
310(2)
Abuses of Statistics
312(1)
When You Are on Your Own
312(1)
Conclusion
313(2)
Appendix A---Math Review and Practice Test 315(5)
Addition, Subtraction, and Negative Numbers
315(1)
Multiplication, Division, and Negative Numbers
316(1)
Statistical Addition: Summation
316(1)
Exponents and Roots
317(1)
Order of Operations
317(1)
Putting It All Together: Simple Math for Statistical Analysis
317(1)
Practice Test
318(2)
Tables 320(7)
Table A-1
320(2)
Table A-2
322(1)
Table A-3
323(1)
Table A-4
324(3)
Appendix B---List of Variables 327(24)
Index 351(12)
Disk Instructions 363

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