Making Sense of Statistics
The book emphasises understanding the reasons behind statistical methods rather than focusing solely on computations or formulae, making it suitable for learners across all disciplines regardless of prior mathematical knowledge. It covers only the essential and widely used statistical techniques typically encountered in introductory courses and research journals, helping readers build a solid foundation before advancing to more complex topics.
In its seventh edition, the book includes updated content such as discussions on observational research methods, new chapters on z-scores, probability, Central Limit Theorem, standard deviation, and regression analyses. It also offers expanded explanations of various t tests, progressive insights into bivariate and multivariate statistics, and improved pedagogical features like chapter objectives, bolded key terms with definitions, and a comprehensive glossary for quick reference.
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Making Sense of Statistics
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Making Sense of Statistics is the ideal introduction to the concepts of descriptive and inferential statistics for students undertaking their first research project. It presents each statistical concept in a series of short steps, then uses worked examples and exercises to enable students to apply their own learning.
Making Sense of Statistics is the ideal introduction to the concepts of descriptive and inferential statistics for students undertaking their first research project. It presents each statistical concept in a series of short steps, then uses worked examples and exercises to enable students to apply their own learning.
It focuses on presenting the why as well as the how of statistical concepts, rather than computations and formulae, so is suitable for students from all disciplines regardless of mathematical background. Only statistical techniques that are almost universally included in introductory statistics courses, and widely reported in journals, have been included. Once students understand and feel comfortable with the statistics that meet these criteria, they should find it easy to master additional statistical concepts.
New to the Seventh Edition:
Retaining the key features and organization that have made this book an indispensable text for teaching and learning the basic concepts of statistical analysis, this new edition features:
- Discussion of the use of observation in quantitative and qualitative research.
- The inclusion of introductions to the book, and each Part.
- Section objectives listed at the beginning of each section to guide the reader.
- New material on key topics such as z-scores, probability, Central Limit Theorem, Standard Deviation, and simple and multiple regression.
- Expanded discussion on t test with separate sections for independent and dependent samples t tests, as well as one-sample t test.
- Progressive analysis of bivariate vs multivariate statistics (starts with the basic concepts and moves to more complex analysis as the student progresses).
- Updated and extended pedagogical material such as Chapter Objectives, exercises, and worked examples to test and enhance student's understanding of the material presented in the chapter.
- Bolded key terms, with definitions and a Glossary for quick referral.
- Expanded Appendices include a brief reference list of some common computational formulas and examples.
- A Glossary of key terms has been added at the end of the book, with references to sections in parenthesis.
- New online instructor resources for classroom use consisting of test bank questions and PowerPoint slides, plus material on basic math review.
Book Details
INFORMATION
ISBN: 9781138894778
Publisher: Taylor & Francis Ltd
Format: Hardback
Date Published: 12 June 2018
Country: United Kingdom
Imprint: Routledge
Edition: 7th edition
Illustration: 26 Tables, black and white; 21 Line drawings, black and white; 21 Illustrations, black and white
Audience: Tertiary education
DIMENSIONS
Width: 210.0mm
Height: 280.0mm
Weight: 816g
Pages: 240
About the Author
Dr Deborah M. Oh is professor in Research Methods and Statistics at California State University, Los Angeles since 1998. She earned her PhD from Columbia University, New York and teaches statistics to a diverse student population in both undergraduate and graduate levels.
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