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Simple Statistics: Applications in Criminology and Criminal Justice

Autor Terance D. Miethe
en Limba Engleză Paperback – 15 sep 2006
Simple Statistics 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; instead, 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 illustrates how verbal statements and other types of information are converted into statistical codes, measures, and variables. While most statistics texts emphasize how to do statistical procedures, they often neglect to explain why we do them. This unique book covers both areas, and the problems at the end of each chapter focus on applications, offering even more context for "why we do" these procedures. Simple Statistics uses hand computation methods to demonstrate how to apply the various statistical procedures, and most chapters include an optional section on how to do these procedures in SPSS and/or Microsoft Excel spreadsheets. Helpful examples illustrate each statistical procedure, and 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.
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Specificații

ISBN-13: 9780195330717
ISBN-10: 0195330714
Pagini: 336
Ilustrații: figures & tables
Dimensiuni: 164 x 238 x 24 mm
Greutate: 0.5 kg
Editura: Oxford University Press
Colecția OUP USA
Locul publicării:New York, United States

Recenzii

What makes Simple Statistics distinctive is its remarkable balance between extremely technical statistics texts that are not written in a student-friendly fashion and oversimplified texts. Miethe writes in an exceptionally readable style, challenging students without intimidating them. Another key strength is the book's use of actual crime data, demonstrating the real-world applications of major statistical concepts.
Throughout this book, the author explains the relevance of statistical techniques

Cuprins

  • 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
  • 2. Garbage In, Garbage Out (GIGO)
  • Measurement Invalidity
  • Sampling Problems
  • Faulty Causal Inferences
  • Political Influences
  • Human Fallibility
  • 3. Issues in Data Preparation
  • Why Is Data Preparation Important?
  • Operationalization and Measurement
  • Coding and Inputting Statistical Data
  • Available Computer Software for Basic Data Analysis
  • 4. Displaying Data in Tables and Graphic Forms
  • The Importance of Data Tables and Graphs
  • Types of Tabular and Visual Presentations
  • Hazards and Distortions in Visual Displays and Collapsing Categories
  • 5. Modes, Medians, Means, and More
  • Modes and Modal Categories
  • The Median and Other Measures of Location
  • The Mean and Its Meaning
  • Choice of Measure of Central Tendency and Position
  • 6. Measures of Variation and Dispersion
  • The Range of Scores
  • The Variance and Standard Deviation
  • Population Versus Sample Variances and Standard Deviations
  • 7. The Normal Curve and Sampling Distributions
  • The Normal Curve
  • Z-Scores as Standard Scores
  • Reading a Normal Curve Table
  • Other Sampling Distributions
  • 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
  • Confidence Intervals: Small Samples
  • 9. Introduction to Hypothesis Testing
  • Confidence Intervals Versus Hypothesis Testing
  • Basic Terminology and Symbols
  • 10. Hypothesis Testing for Means and Proportions
  • Types of Hypothesis Testing
  • Issues in Testing Statistical Hypotheses
  • 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 Rules for Interpreting a Contingency Table
  • Specifying Causal Relations in Contingency Tables
  • Assessing the Magnitude of Bivariate Associations in Contingency Tables
  • Issues in Contingency Table Analysis
  • 12. The Analysis of Variance (ANOVA)
  • Overview of ANOVA and When It Is Used
  • Partitioning Variation into Between- and Within-Group Differences
  • Hypothesis Testing and Measures of Association in ANOVA
  • Issues in the Analysis of Variance
  • 13. Correlation and Regression
  • The Scatterplot of Two Interval or Ratio Variables
  • The Correlation Coefficient Regression Analysis
  • Issues in Bivariate Regression and Correlation Analysis
  • 14. Introduction to Multivariate Analysis
  • Why Do Multivariate Analysis?
  • Types of Multivariate Analysis