Behavioral Research Data Analysis with R
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From the reviews:
“The target audience is behavioural scientists who wish to move to using R for some or all of their analyses. … There is a good balance between discussion of the scientific background, the processing of data, R coding issues, and discussion of results. Extensive references are provided, both for sources of the data and for methodology. … For a senior student or researcher … this text is strongly recommended.” (John H. Maindonald, International Statistical Review, Vol. 82 (1), 2014)»
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. Les mer
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This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely-used statistical methods in behavioral research, using a set of notes and annotated examples. The book will also help beginners learn more about statistics and behavioral research. These are statistical techniques used by psychologists who do research on human subjects, but of course they are also relevant to researchers in others fields that do similar kinds of research.
The authors emphasize practical data analytic skills so that they can be quickly incorporated into readers' own research.
The authors emphasize practical data analytic skills so that they can be quickly incorporated into readers' own research.
Detaljer
- Forlag
- Springer-Verlag New York Inc.
- Innbinding
- Paperback
- Språk
- Engelsk
- Sider
- 245
- ISBN
- 9781461412373
- Utgivelsesår
- 2011
- Format
- 24 x 16 cm
Anmeldelser
«
From the reviews:
“The target audience is behavioural scientists who wish to move to using R for some or all of their analyses. … There is a good balance between discussion of the scientific background, the processing of data, R coding issues, and discussion of results. Extensive references are provided, both for sources of the data and for methodology. … For a senior student or researcher … this text is strongly recommended.” (John H. Maindonald, International Statistical Review, Vol. 82 (1), 2014)»
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