Statistics for Criminology and Criminal Justice,9780072518443

Statistics for Criminology and Criminal Justice

by ;
Edition: 2nd
ISBN13: 9780072518443
ISBN10: 0072518448
Format: Hardcover
Pub. Date: 2003-08-05
Publisher(s): McGraw-Hill Humanities/Social Sciences/Languages
List Price: $159.75

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Summary

This is the only book that introduces students to the statistical methods of criminology and criminal justice and shows how they are actually used. Each detailed yet accessible chapter combines instruction in statistical analysis with investigations of key research questions in the field; for example, what are the causes of crime? Useful at both the introductory and intermediate levels, the text contains in-depth coverage of descriptive statistics, including graphical displays of data and exploratory data analysis, along with bivariate and multivariate analyses. Emphasis is placed equally on calculation and interpretation.

Table of Contents

CHAPTER 1 The Purpose of Statistics in the Criminological Sciences 1(24)
Introduction
2(2)
Setting the Stage for Statistical Inquiry
4(1)
The Role of Statistical Methods in Criminology and Criminal Justice
5(5)
Descriptive Research Case Study: The Magnitude of Youth Violence
6(1)
Explanatory Research Case Study: The Causes of Youth Violence
7(2)
Evaluation Research Case Study: School Programs to Prevent Youth Violence
9(1)
Validity in Criminological Research
10(3)
Measurement Validity
10(2)
Causal Validity
12(1)
Generalizability
12(1)
Populations and Samples
13(2)
Techniques of Sampling
15(1)
Probability Sampling Techniques
16(3)
Simple Random Samples
16(1)
Systematic Random Samples
17(1)
Multistage Cluster Samples
17(1)
Weighted Samples
18(1)
Nonprobability Sampling Techniques
19(3)
Quota Samples
20(1)
Purposive or Judgment Samples
20(1)
Availability Samples
21(1)
Descriptive and Inferential Statistics
22(1)
Summary
23(1)
Key Terms
23(1)
Practice Problems
24(1)
SPSS Practice Problems
24(1)
PART 1 Univariate Analysis: Describing Variable Distributions
CHAPTER 2 Levels of Measurement and Aggregation
25(24)
Introduction
26(1)
Levels of Measurement
27(10)
Nominal Measurement
30(1)
Ordinal Measurement
31(1)
Interval Measurement
32(2)
Ratio Measurement
34(3)
Independent and Dependent Variables
37(2)
Case Study: General Strain Theory and Crime
38(1)
Ways of Presenting Variables
39(3)
Counts and Rates
39(1)
Case Study: The Importance of Rates for Crime Data
40(2)
Proportions and Percents
42(1)
Units of Analysis
42(2)
Summary
44(1)
Key Terms
45(1)
Key Formulas
46(1)
Practice Problems
46(1)
SPSS Practice Problems
47(2)
CHAPTER 3 Understanding Data Distributions: Tabular and Graphical Techniques
49(52)
Introduction
50(4)
Case Study: The Defense of John Gotti
54(1)
The Tabular and Graphical Display of Qualitative Data
54(9)
An Analysis of Hate Crimes Using Tables
54(2)
Pie Charts and Bar Charts
56(7)
The Tabular and Graphical Display of Quantitative Data
63(1)
Ungrouped Distributions
63(7)
Grouped Distributions
70(13)
The Shape of a Distribution
83(2)
Time Plots
85(7)
A Trend Analysis of Crime Rates
86(6)
Summary
92(1)
Key Terms
93(1)
Key Formulas
93(1)
Practice Problems
94(5)
SPSS Practice Problems
99(2)
CHAPTER 4 Measures of Central Tendency
101(33)
Introduction
102(1)
The Mode
103(7)
The Modal Category of Hate Crime
104(2)
The Modal Number of Prior Arrests
106(2)
Advantages and Disadvantages of the Mode
108(2)
The Median
110(6)
Calculating the Median Number of Prior Convictions
111(2)
The Median for Grouped Data
113(2)
Advantages and Disadvantages of the Median
115(1)
The Mean
116(10)
Calculating the Mean
117(2)
Calculating the Mean Police Response Time
119(2)
The Mean for Grouped Data
121(4)
Advantages and Disadvantages of the Mean
125(1)
Summary
126(1)
Key Terms
127(1)
Key Formulas
127(1)
Practice Problems
128(4)
SPSS Practice Problems
132(2)
CHAPTER 5 Measures of Dispersion
134(53)
Introduction
135(2)
Measuring Dispersion for Nominal- and Ordinal Level Variables
137(3)
The Variation Ratio
137(3)
Measuring Dispersion for Interval-/ or Ratio-Level Variables
140(28)
The Range and Interquartile Range
140(1)
Calculating the Range of Sentence Lengths
140(4)
Calculating the Interquartile Range of the Number of Escapes by Prison
144(3)
The Standard Deviation and Variance
147(6)
Calculating the Variance and Standard Deviation of a Sample with Ungrouped Data: The Variation in Judges' Sentences
153(6)
Calculating the Variance and Standard Deviation of a Sample with Grouped Data
159(4)
Computational Formulas for Variance and Standard Deviation
163(5)
Graphing Dispersion with Exploratory Data Analysis
168(11)
Constructing Boxplots
168(1)
Constructing a Boxplot for Felony Conviction Data
169(7)
Constructing a Boxplot for Prisoners Sentenced to Death
176(3)
Summary
179(1)
Key Terms
179(1)
Key Formulas
180(2)
Practice Problems
182(3)
SPSS Practice Problems
185(2)
PART 2 Making Inferences in Univariate Analysis: Generalizing from a Sample to a Population
CHAPTER 6 Probability, Probability Distributions, and an Introduction to Hypothesis Testing
187(57)
Introduction
188(1)
Probability
188(2)
The Rules of Probability
190(13)
Citizen Perceptions about Justice
192(11)
Probability Distributions
203(3)
A Discrete Probability Distribution-The Binomial Distribution
206(4)
Hypothesis Testing with the Binomial Distribution
210(9)
Predicting the Probability of Car Theft
210(9)
A Continuous Probability Distribution-The Standard Normal Distribution
219(10)
The Area Under the Normal Curve
222(2)
The Standard Normal Distribution and Standard Scores
224(5)
Samples, Populations, Sampling Distributions, and the Central Limit Theorem
229(8)
Summary
237(1)
Key Terms
238(1)
Key Formulas
239(1)
Practice Problems
239(4)
SPSS Practice Problems
243(1)
CHAPTER 7 Point Estimation and Confidence Intervals
244(28)
Introduction
245(3)
Properties of Good Estimates
248(2)
Estimating a Population Mean from Large Samples
250(7)
Estimating Alcohol Consumption
252(1)
Estimating the Onset of Crack/Cocaine Use
253(4)
Estimating Confidence Intervals from Small Samples
257(8)
Estimating the Effects of Arrest on Employment
259(2)
Estimating Rape Offending Patterns
261(4)
Estimating Confidence Intervals for Proportions and Percents
265(3)
Estimating the Effects of Community Policing
265(1)
Estimating Gender Differences on Attitudes toward Crime Control
266(2)
Summary
268(1)
Key Terms
268(1)
Key Formulas
269(1)
Practice Problems
269(1)
SPSS Practice Problems
270(2)
CHAPTER 8 From Estimation to Statistical Tests: Hypothesis Testing for One Population Mean and Proportion
272(37)
Introduction
273(2)
Testing a Hypothesis about a Single Population Mean: The z Test
275(13)
Case Study: Testing the Mean Reading Levels from a Prison Literacy Program
275(5)
Case Study: Foot Patrols and Crime Rates
280(5)
Case Study: Testing the Mean Sentence Length for Robbery
285(3)
Directional and Nondirectional Hypothesis Tests
288(6)
Case Study: Mean Socialization Levels of Offenders
292(2)
Hypothesis Testing for Population Means Using Small Samples: The t test
294(5)
Case Study: Deadbeat Dads
296(3)
Hypothesis Testing for Population Proportions and Percents Using Large Samples
299(6)
Case Study: Attitudes toward Gun Control
301(2)
Case Study: Random Drug Testing of Inmates
303(2)
Summary
305(1)
Key Terms
305(1)
Key Formulas
305(1)
Practice Problems
306(2)
SPSS Practice Problems
308(1)
PART 3 Bivariate Analysis: Relationships between Two Variables
CHAPTER 9 Testing Hypotheses with Categorical Data
309(57)
Introduction
310(1)
The One Variable Goodness of Fit Chi-Square Test
311(9)
Case Study: Satisfaction with Police Services
311(9)
Contingency Tables and the Two Variable Chi-Square Test of Independence
320(7)
Case Study: Gender and Emotions
320(5)
Case Study: Liking School and Delinquency
325(2)
The Chi-Square Test of Independence
327(7)
A Simple-to-Use Computational Formula for the Chi-Square Test of Independence
334(10)
Case Study: Socioeconomic Status of Neighborhoods and Police Response Time
335(9)
Measures of Association: Determining the Strength of the Relationship between Two Categorical Variables
344(13)
Nominal-Level Variables
344(5)
Ordinal-Level Variables
349(8)
Summary
357(1)
Key Terms
358(1)
Key Formulas
358(1)
Practice Problems
359(5)
SPSS Practice Problems
364(2)
CHAPTER 10 Hypothesis Tests Involving Two Population Means or Proportions
366(45)
Explaining the Difference between Two Sample Means
367(3)
Sampling Distribution of Mean Differences
370(3)
Testing a Hypothesis about the Difference between Two Means: Independent Samples
373(26)
Model 1: Pooled Variance Estimate (σ1=σ2)
374(9)
Model 2: Separate Variance Estimate (&)
383(6)
Matched-Groups or Dependent Samples t Test
389(3)
Case Study: Problem-Oriented Policing and Crime
392(5)
Case Study: Siblings and Delinquency
397(2)
Hypothesis Tests for the Difference between Two Proportions: Large Samples
399(6)
Case Study: Education and Recidivism
402(3)
Summary
405(1)
Key Terms
405(1)
Key Formulas
405(1)
Practice Problems
406(3)
SPSS Practice Problems
409(2)
CHAPTER 11 Hypothesis Tests Involving Three or More Population Means: Analysis of Variance
411(34)
Introduction
412(1)
The Logic of Analysis of Variance
413(2)
Case Study: Police Responses to Domestic Violence
413(2)
Total, Between-Group, and Within-Group Variance
415(6)
Conducting a Hypothesis Test with ANOVA
421(5)
After the F Test: Testing the Difference between Pairs of Means
426(2)
A Measure of Association with ANOVA
428(2)
A Second ANOVA Example: Adolescent Employment and Delinquency
430(3)
A Third ANOVA Example: Region of the Country and Homicide
433(5)
Summary
438(1)
Key Terms
438(1)
Key Formulas
438(1)
Practice Problems
439(4)
SPSS Practice Problems
443(2)
CHAPTER 12 Bivariate Correlation and Regression
445(61)
Graphing the Bivariate Distribution between Two Quantitative Variables: Scatterplots
446(14)
Case Study: Causes of State-Level Crime
455(5)
Pearson Correlation Coefficient
460(6)
Interpreting a Correlation: The Coefficient of Determination
466(1)
The Least-Squares Regression Line
467(16)
Case Study: Age and Delinquency
467(9)
Using the Regression Line for Prediction
476(1)
Case Study: Predicting State Crime Rates
476(7)
Comparison of b and r
483(3)
Testing for the Significance of b and r
486(5)
Case Study: Murder and Poverty
489(1)
Case Study: Violent Crime and Rural Population
490(1)
Case Study: Violent Crime and Divorce
490(1)
The Problems of Limited Variation, Nonlinear Relationships, and Outliers in the Data
491(6)
Summary
497(2)
Key Terms
499(1)
Key Formulas
499(1)
Practice Problems
500(3)
SPSS Practice Problems
503(3)
PART 4 Multivariate Analysis: Relationships between More than Two Variables
CHAPTER 13 Controlling for a Third Variable: Multiple Regression and Partial Correlation
506(45)
Controlling for Other Important Variables to Determine Causation
507(2)
Illustrating Statistical Control with Partial Tables
508(1)
The Multiple Regression Equation
509(11)
Predicting Delinquency
513(7)
Beta Weights
520(2)
Partial Correlation Coefficients
522(6)
Multiple Coefficient of Determination, R2
524(1)
Calculating Change in R2
525(3)
Hypothesis Testing in Multiple Regression
528(6)
Another Example: Prison Density, Mean Age, and Rate of Inmate-to-Inmate Assault
534(9)
Summary
543(1)
Key Terms
543(1)
Key Formulas
543(1)
Practice Problems
544(5)
SPSS Practice Problems
549(2)
CHAPTER 14 Regression Analysis with a Dichotomous Dependent Variable: Logit and Probit Models
551(57)
Introduction
552(1)
Estimating an OLS Regression Model with a Dichotomous Dependent Variable-The Linear Probability Model
553(6)
Case Study: Age of First Delinquent Offense and Adult Criminality
553(6)
The Logit Regression Model with One Independent Variable
559(17)
Predicted Probabilities in Logit Models
579
Significance Testing for Logistic Regression Coefficients
568(2)
Model Goodness-of-Fit Measures
570(2)
Case Study: Race and Capital Punishment
572(4)
The Probit Regression Model with One Independent Variable
576(8)
Case Study: Age of First Delinquent Offense and Adult Criminality
576(3)
Predicted Probabilities in Probit Models
579(1)
Significance Testing for Probit Coefficients
580(1)
Model Goodness-of-Fit Measures
581(1)
Case Study: Race and Capital Punishment
581(3)
Logistic Regression Models with Two Independent Variables
584(13)
Case Study: Age at Which Delinquency First Occurs and Gender
584(7)
Case Study: Race of Victim, the Brutality of a Homicide, and Capital Punishment
591(6)
Probit Regression Models with Two Independent Variables
597(6)
Case Study: Age at Which Delinquency First Occurs and Gender
597(4)
Case Study: Race of Victim, the Brutality of a Homicide, and Capital Punishment
601(2)
Summary
603(1)
Key Terms
604(1)
Key Formulas
604(1)
Practice Problems
605(2)
SPSS Practice Problems
607
PART 5 References
APPENDIX A Review of Basic Mathematical Operations
608(12)
APPENDIX B An Introduction to SPSS 11.0
620(29)
APPENDIX C Solutions to Problems
649(61)
APPENDIX D Codebooks to Data Sets
710(11)
APPENDIX E Statistical Tables
721(10)
APPENDIX F References
731
Index I-1

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