SPSS survival manual : a step by step guide to data analysis using IBM SPSS
著者
書誌事項
SPSS survival manual : a step by step guide to data analysis using IBM SPSS
Open University Press, 2021
7th ed
- : pbk
大学図書館所蔵 全7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
First published 2001
Includes bibliographical references (p. 353-357) and index
内容説明・目次
内容説明
The SPSS Survival Manual throws a lifeline to students and researchers grappling with this powerful data analysis software.
In her bestselling guide, Julie Pallant takes you through the entire research process, helping you choose the right data analysis technique for your project. This edition has been updated to include up to SPSS version 26. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, Julie discusses basic and advanced statistical techniques. She outlines each technique clearly, with step-by-step procedures for performing the analysis, a detailed guide to interpreting data output and an example of how to present the results in a report.
For both beginners and experienced users in Psychology, Sociology, Health Sciences, Medicine, Education, Business and related disciplines, the SPSS Survival Manual is an essential text. It is illustrated throughout with screen grabs, examples of output and tips, and is also further supported by a website with sample data and guidelines on report writing.
This seventh edition is fully revised and updated to accommodate changes to IBM SPSS procedures.
目次
Preface
Data files and website
Introduction and overview
Part One Getting started
1 Designing a study
2 Preparing a codebook
3 Getting to know IBM SPSS Statistics
Part Two Preparing the data file
4 Creating a data file and entering data
5 Screening and cleaning the data
Part Three Preliminary analyses
6 Descriptive statistics
7 Using graphs to describe and explore the data
8 Manipulating the data
9 Checking the reliability of a scale
10 Choosing the right statistic
Part Four Statistical techniques to explore relationships among variables
11 Correlation
12 Partial correlation
13 Multiple regression
14 Logistic regression
15 Factor analysis
Part Five Statistical techniques to compare groups
16 Non-parametric statistics
17 T-tests
18 One-way analysis of variance
19 Two-way between-groups ANOVA
20 Mixed between-within subjects analysis of variance
21 Multivariate analysis of variance
22 Analysis of covariance
Appendix: Details of data files
Recommended reading
References
Index
「Nielsen BookData」 より