Crime statistics are everywhere, but how do you know when they’re valid? If a newspaper report says "the rate of overall violent crime decreased by 0.9 percent," how can you tell where that statistic came from, what it measures, and how accurate it is? Is it worth repeating or sharing? Measuring Crime: Behind the Statistics gives you the tools to interpret and evaluate crime statistics’ quality and usefulness.
From the back cover:
What is the unemployment rate? How many adults have high blood pressure? What is the total area of land planted with soybeans? Sampling: Design and Analysis tells you how to design and analyze surveys to answer these and other questions. This authoritative text, used as a standard reference by numerous survey organizations, teaches sampling using real data sets from social sciences, public opinion research, medicine, public health, economics, agriculture, ecology, and other fields.
The book is accessible to students from a wide range of statistical backgrounds. By appropriate choice of sections, it can be used for a graduate class for statistics students or for a class with students from business, sociology, psychology, or biology. Readers should be familiar with concepts from an introductory statistics class including linear regression; optional sections contain the statistical theory, for readers who have studied mathematical statistics.
Distinctive features include:
More than 450 exercises. In each chapter, Introductory Exercises develop skills, Working with Data Exercises give practice with data from surveys, Working with Theory Exercises allow students to investigate statistical properties of estimators, and Projects and Activities Exercises integrate concepts. A solutions manual is available.
An emphasis on survey design.
Coverage of simple random, stratified, and cluster sampling; ratio estimation; constructing survey weights; jackknife and bootstrap; nonresponse; chi-squared tests and regression analysis.
Graphing data from surveys.
Computer code using SAS® software.
Online supplements containing data sets, computer programs, and additional material.
Table of Contents
Introduction / 1
Simple Probability Samples / 25
Stratified Sampling / 73
Ratio and Regression Estimation / 117
Cluster Sampling with Equal Probabilities / 165
Sampling with Unequal Probabilities / 219
Complex Surveys / 281
Nonresponse / 329
Variance Estimation in Complex Surveys / 365
Categorical Data Analysis in Complex Surveys / 401
Regression with Complex Survey Data / 429
Two-Phase Sampling / 469
Estimating Population Size / 495
Rare Populations and Small Area Estimation / 511
Survey Quality / 527
Probability Concepts Used in Sampling / 549
References / 563
Author Index / 587
Subject Index / 592