Simple Statistics Applications in Criminology and Criminal Justice

ISBN-10: 0195330714
ISBN-13: 9780195330717
Edition: N/A
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Description: 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  More...

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Book details

List price: $85.95
Publisher: Oxford University Press, Incorporated
Publication date: 9/15/2006
Binding: Paperback
Pages: 336
Size: 7.00" wide x 9.00" long x 0.75" tall
Weight: 1.496
Language: English

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.

Terance Miethe received his Ph.D. in Sociology from Washington State University, and is currently a Professor of Criminal Justice at the University of Nevada-Las Vegas. He is the author of several books and research articles in the areas of criminal victimization, theories of crime, and criminal processing.

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
Garbage In, Garbage Out (GIGO)
Measurement Invalidity
Sampling Problems
Faulty Causal Inferences
Political Influences
Human Fallibility
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
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
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
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
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
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 for Population Means
Confidence Intervals for Population Proportions
Confidence Intervals: Small Samples
Properties of the t-Distribution
Confidence Intervals for Population Means
Confidence Intervals for Population Proportions
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
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
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 Magnitud

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