Introductory Statistics for Criminal Justice and Criminology

ISBN-10: 0130142921

ISBN-13: 9780130142924

Edition: 2002

Authors: Jon L. Proctor, Diane M. Badzinski

List price: $180.00
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Book details

List price: $180.00
Copyright year: 2002
Publisher: Prentice Hall PTR
Publication date: 5/29/2001
Binding: Paperback
Pages: 480
Size: 7.00" wide x 9.25" long x 1.00" tall
Weight: 1.936

List of Figures and Tables
Preface
Acknowledgments
About the Authors
Purpose of Statistics
Studying Crime and Taking Statistics
Descriptive and Inferential Statistics
From Samples to Populations
Mathematical Operations
Computer Technology and Statistics
Summary
Foundations of Research
Goals of Science
Variables and Attributes
Levels of Measurement
Nominal Level
Ordinal Level
Interval Level
Ratio Level
Hypothesis Construction
Role of Theory
Summary
Problems
Data Organization
Data Distributions
Single Data Distribution
Frequency Distribution
Grouped Frequency Distribution
Descriptive Statistics
Proportions
Percentages
Ratios
Rates
Cross-tabulations
Using Excel to Compute Descriptive Statistics
Proportions
Percentages
Cumulative Percentage
Cumulative Frequency
Rates
Graphical Representation of Data
Histograms
Bar Graphs
Line Graphs
Pie Charts
Summary
Problems
Measures of Central Tendency
Single Data Distribution
Mode
Median
Mean
Frequency Distribution
Mode
Median
Mean
Grouped Data Distribution
Mode
Median
Mean
Using Excel to Compute Measures of Central Tendency
Single Data Distribution
Frequency Distribution
Grouped Data Distribution
Selecting a Measure of Central Tendency
Level of Measurement
Shape of Distribution
Comparison of the Mode, Median, and Mean
Summary
Problems
Measures of Dispersion
Single Data Distribution
Range
Variance
Standard Deviation
Frequency Distribution
Range
Variance
Standard Deviation
Grouped Data Distribution
Variance
Standard Deviation
Using Excel to Compute Measures of Dispersion
Single Data Distribution
Frequency Distribution
Grouped Data Distribution
Usefulness of the Standard Deviation
Characteristics of the Standard Deviation
Interpreting the Standard Deviation
Summary
Problems
Probability Theory
Basic Concepts of Probability Theory
Probability Distribution
The Normal Curve
Properties of the Normal Curve
Area Under the Normal Curve
Standardized Scores (z)
Probability and the Normal Curve
Using Excel to Calculate z-Scores
Summary
Problems
Sample Statistics to Population Parameters
Sample Statistics and Population Parameters
Probability Sampling
Types of Probability Samples
Sampling Error
Sampling Distribution
Estimating a Population Mean ([mu]) Using the z Distribution
Confidence Levels
Confidence Intervals
Estimating a Population Mean ([mu]) Using the t Distribution
Estimating a Population Proportion ([pi]) Using the z Distribution
Using Excel to Construct Confidence Intervals
Confidence Intervals for a Population Mean ([mu]) Using z
Confidence Intervals for a Population Mean ([mu]) Using t
Confidence Interval for a Population Proportion ([pi]) Using z
Summary
Problems
Statistical Analysis for a Population Mean and Proportion: z Tests
The Logic of Hypothesis Testing
Nondirectional and Directional Hypotheses
Decision Making about the Null Hypothesis
Significance Level
Comparing the Test Statistic to the Probability Distribution
One-Sample z Test
Procedures for Calculating a One-Sample z Test
z Test for Proportions
Using Excel to Compute z Tests
One-Sample z Test
z Test for Proportions
Assumptions of z Tests
Summary
Problems
Statistical Analysis for Nominal and Ordinal Variables: Chi-Square and Spearman's Rho
Chi-Square: Introduction
One-Sample Chi-Square
Procedures for Calculating the One-Sample Chi-Square
Two-Sample Chi-Square
Procedures for Calculating the Two-Sample Chi-Square
Measures of Association: Phi Coefficient and Cramer's V
Phi Coefficient ([Phi])
Cramer's V
Spearman's Rank-Order Correlation Coefficient
Procedures for Calculating Spearman's Rho
Using Excel to Compute Chi-Square and Spearman's Rho
Two-Sample Chi-Square
Spearman's Rho
Summary
Problems
Statistical Analysis for Comparing Two Population Means: t Tests
Independent-Samples t Test
Procedures for Independent-Samples t Test
Dependent- or Matched-Samples t Test
Procedures for Dependent- or Matched-Samples t Statistic
Assumptions of the t Test
Using Excel to Compute t Tests
Independent-Samples t Test
Dependent-Samples t Test
Summary
Problems
Statistical Analysis for Comparing Three or More Population Means: Analysis of Variance
Comparison of t Statistic and ANOVA
Assumptions of ANOVA
Single-Factor ANOVA
Procedures for Calculating a Single-Factor ANOVA
Post Hoc Comparisons
Procedures for Calculating Tukey's HSD Test
Repeated-Measures ANOVA
Two-Factor ANOVA
Using Excel to Compute Analysis of Variance
Tukey's HSD
Repeated-Measures ANOVA
Two-Factor ANOVA
Summary
Problems
Statistical Analysis for Assessing Relationships: Correlation
Nature of Correlation
Interpreting Correlation Coefficients
Pearson's Correlation Coefficient (r)
Procedures for Calculating Pearson's Product-Moment
Correlation Coefficient
Using Scatterplots in Correlation Analysis
Coefficients of Determination and Nondetermination
Partial Correlation Coefficient
Procedures for Calculating a Partial Correlation Coefficient
Using Excel for Correlation Analysis
Pearson's r
Partial Correlation Coefficient
Summary
Problems
Statistical Analysis for Prediction: Regression
The Regression Equation
The Regression Line
Calculating the Slope (b) and the Intercept (a)
Procedures for Regression Analysis
Residual Error
Multiple Regression Analysis
Using Excel for Regression Analysis
Bivariate Regression
Multiple Regression
Summary
Problems
Probability Distribution Tables
z Distribution Table (Normal Curve)
Critical Values of t
Critical Values of r at the .05 and .01 Significance Levels
Critical Values of F at the .05 and .01 Significance Levels
Critical Values of Chi-Square at the .10, .05, .01, and .001 Significance Levels
Critical Values of Studentized Range (q) at the .05 Significance Level
Critical Values of Spearman's Rho (r[subscript s])
Chapter Solutions for Odd Questions
Glossary
Bibliography
Index
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