教育学における定量データ分析<br>Quantitative Data Analysis in Education : A Critical Introduction Using SPSS

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教育学における定量データ分析
Quantitative Data Analysis in Education : A Critical Introduction Using SPSS

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 288 p.
  • 言語 ENG
  • 商品コード 9780415372985
  • DDC分類 370.21

Full Description

This book provides a refreshing and user-friendly guide to quantitative data analysis in education for students and researchers. It assumes absolutely no prior knowledge of quantitative methods or statistics. Beginning with the very basics, it provides the reader with the knowledge and skills necessary to be able to undertake routine quantitative data analysis to a level expected of published research.

Rather than focusing on teaching statistics through mathematical formulae, the book places an emphasis on using SPSS to gain a real feel for the data and an intuitive grasp of the main concepts and techniques involved. Drawing extensively upon up-to-date and relevant examples, the reader will be encouraged to think critically about quantitative research and its potential as well as its limitations in relation to education.

Packed with helpful features, this book:

provides illustrated step-by-step guides showing how to use SPSS, with plenty of exercises to encourage the reader to practice and consolidate their new skills
makes extensive use of real-life educational datasets derived from national surveys in the US and UK to illustrate key points and to bring the material to life
has a companion website that contains all of the educational datasets used in the book to download as well as comprehensive answers to exercises and a range of other useful resources that are regularly updated.

The book will therefore appeal not only to undergraduate and postgraduate students but also to more established and seasoned educational researchers and lecturers and professors who have tended to avoid or shy away from quantitative methods.

Contents

Who is this book for and what is it about? 1. Getting Started with SPSS 2. Exploring, Displaying and Summarising Data 3. Analyzing Relationships Between Variables 4. Good Practice in Presenting Findings 5. Confidence Intervals and Statistical Significance 6. Conducting Statistical Tests and Calculating Effect Sizes 7. Where Next?

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