Statistics in criminal justice
著者
書誌事項
Statistics in criminal justice
Springer, c2007
3rd ed
大学図書館所蔵 全3件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes index
内容説明・目次
内容説明
Statistics in Criminal Justice takes an approach that emphasizes the uses of statistics in research in crime and justice. This text is meant for students and professionals who want to gain a basic understanding of statistics in this field. The text takes a building-block approach, meaning that each chapter helps to prepare the student for the chapters that follow. It also means that the level of sophistication of the text increases as the text progresses. Throughout the text there is an emphasis on comprehension and interpretation, rather than computation. However, it takes a serious approach to statistics, which is relevant to the real world of research in crime and justice. This approach is meant to provide the reader with an accessible but sophisticated understanding of statistics that can be used to examine real-life criminal justice problems. The goal of the text is to give the student a basic understanding of statistics and statistical concepts that will leave the student with the confidence and the tools for tackling more complex problems on their own. Statistics in Criminal Justice is meant not only as an introduction for students but as a reference for researchers.
A number of changes have been made to the 3rd edition, including the following:
- Additional exercises at the end of each chapter
- Expanded computer exercises that can be performed in the Student Version of SPSS
- Extended discussion of multivariate regression models, including interaction and non-linear effects
- A new chapter on multinomial and ordinal logistic regression models, examined in a way that highlights comprehension and interpretation
- With the additional material on multivariate regression models, the text is appropriate for both undergraduate and beginning graduate statistics courses in criminal justice
目次
Introduction: Statistics as a Research Tool.- Measurement: The Basic Building Block of Research.- Representing and Displaying Data.- Describing the Typical Case: Measures of Central Tendency.- How Typical Is the Typical Case?: Measuring Dispersion.- The Logic of Statistical Inference: Making Statements About Populations from Sample Statistics.- Defining the Observed Significance Level of a Test: A Simple Example Using the Binomial Distribution.- Steps in a Statistical Test: Using the Binomial Distribution to Make Decisions About Hypotheses.- Chi-Square: A Test Commonly Used for Nominal-Level Measures.- The Normal Distribution and Its Application to Tests of Statistical Significance.- Comparing Means and Proportions in Two Samples.- Comparing Means Among More Than Two Samples: Analysis of Variance.- Measures of Association for Nominal and Ordinal Variables.- Measuring Association for Interval-Level Data: Pearson's Correlation Coefficient.- An Introduction to Bivariate Regression.- Multivariate Regression.- Multivariate Regression: Additional Topics.- Logistic Regression.- Multivariate Regression with Multiple Category Nominal or Ordinal Measures: Extending the Basic Logistic Regression Model.- Special Topics: Confidence Intervals.- Special Topics: Statistical Power.
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