Simple Statistics: Applications in Criminology and Criminal Justice provides a concise and compelling introduction to basic statistics for students of criminology and criminal justice. Written in a conversational tone, it does not "dumb down" the material; rather, it demonstrates the value of statistical thinking and reasoning in context. The text covers essential techniques instead of attempting to provide an encyclopedic sweep of all statistical procedures. Author Terance D. Miethe shows how verbal statements and other types of information are converted into statistical codes, measures, and variables. Many texts don't cover this process of operationalization and measurement, so most students have no idea how research methods and statistics are related or how to conduct statistical analysis from the bottom up. While most statistics texts emphasize how to do statistical procedures and neglect why we do them, this unique book covers both areas. The problems at the end of each chapter focus on applications, offering more context for "why we do" these procedures. The term informed consumer is frequently used to convey the importance of understanding social statistics for becoming a better student, employee, and citizen. Simple Statistics uses hand computation methods to demonstrate how to apply the various statistical procedures. Most chapters also contain an optional section on how to do these procedures in SPSS and/or Microsoft Excel spreadsheets, but such applications are not necessary for understanding the statistical methods described in this book. Several examples--but not an overwhelming amount--are used to illustrate each statistical procedure. Specific problems, detailed summaries, key terms, and major formulas are provided at the end of each chapter to further highlight major points. A comprehensive Instructor's Manual is also available.

CHAPTER 1: INTRODUCTION TO STATISTICAL THINKING Some Definitions and Basic Ideas Math Phobia, Panic, and Terror in Social Statistics The Practical Value of Social Statistics and Statistical Reasoning Types of Statistical Methods Pedagogical (Teaching) Approaches

CHAPTER 2: GARBAGE IN, GARBAGE OUT (GIGO) Measurement Invalidity Sampling Problems Faulty Causal Inferences Political Influences Human Fallibility

CHAPTER 3: ISSUES IN DATA PREPARATION Why Is Data Preparation Important? Operationalization and Measurement Nominal Measurement of Qualitative Variables Measurement of Quantitative Variables Issues in Levels of Measurement Coding and Inputting Statistical Data Available Computer Software for Basic Data Analysis

CHAPTER 4: DISPLAYING DATA IN TABLES AND GRAPHIC FORMS The Importance of Data Tables and Graphs Types of Tabular and Visual Presentations Tables and Graphs for Qualitative Variables Tables and Graphs for Quantitative Variables Ratios and Rates Maps of Qualitative and Quantitative Variables Hazards and Distortions in Visual Displays and Collapsing Categories

CHAPTER 5: MODES, MEDIANS, MEANS, AND MORE Modes and Modal Categories The Median and Other Measures of Location The Mean and Its Meaning Weighted Means Strengths and Limitations of Mean Ratings Choice of Measure of Central Tendency and Position

CHAPTER 6: MEASURES OF VARIATION AND DISPERSION The Range of Scores The Variance and Standard Deviation Variances and Standard Deviations for Binary Variables Population Versus Sample Variances & Standard Deviations

CHAPTER 7: THE NORMAL CURVE AND SAMPLING DISTRIBUTIONS The Normal Curve Z-Scores as Standard Scores Reading a Normal Curve Table Other Sampling Distributions Binomial Distribution t-Distribution Chi-Square Distribution F-Distributions

CHAPTER 8: PARAMETER ESTIMATION AND CONFIDENCE INTERVALS Sampling Distributions and the Logic of Parameter Estimation Inferences from Sampling Distributions to One Real Sample Confidence Intervals: Large Samples, ? Known Confidence Intervals for Population Means Confidence Intervals for Population Proportions Confidence Intervals: Small Samples and Unknown ? Properties of the t-Distribution Confidence Intervals for Population Means for Unknown ? Confidence Intervals for Population Proportions for Unknown ?

CHAPTER 9: INTRODUCTION TO HYPOTHESIS TESTING Confidence Intervals Versus Hypothesis Testing Basic Terminology and Symbols Types of Hypotheses Zone of Rejection and Critical Values Significance Levels and Errors in Decision Making

CHAPTER 10: HYPOTHESIS TESTING FOR MEANS AND PROPORTIONS Types of Hypothesis Testing One-Sample Tests of the Population Mean One-Sample Tests of a Population Proportion Two Sample Test of Differences in Population Means Two Sample Test of Differences in Population Proportions Issues in Testing Statistical Hypotheses

CHAPTER 11: STATISTICAL ASSOCIATION IN CONTINGENCY TABLES The Importance of Statistical Association and Contingency Tables The Structure of a Contingency Table Developing Tables of Total, Row, and Column Percentages The