Exploring statistics with Minitab : a workbook for the behavioural sciences

著者

書誌事項

Exploring statistics with Minitab : a workbook for the behavioural sciences

Andrew Monk

Wiley, c1991

  • : paper/spiral bound

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注記

Includes index

内容説明・目次

内容説明

The availability of statistical packages on mainframe and micro computers has made what were previously considered quite advanced statistical techniques, such as multiple regression or the analysis of covariance, accessible to many more students taking courses in psychology and ergonomics. For the same reason these and simpler techniques such as correlation and significance testing are included in courses for students in other behavioural sciences such as sociology and linguistics. This book is for all those students. It is based on three assumptions including: that the reader has a practical interest in using statistical tests rather than a theoretical interest in their derivation, that statistical procedures are best learned by doing, and that the reader will use the book in conjunction with a statistical package. In this connection the "work sheets", where the reader explores the statistical concepts under consideration, are an important part of the book. The reader works through directions to perform computations and two minute exercises to check a point is understood before moving on to the next. By its nature a work sheet can only be effective if the commands required, and the responses from the computer which will result, are known by the author i.e., the book has to be written for a particular statistics package. The package chosen has to be widely available and have all the functions and tests needed. Minitab meets these requirements, for example, it can compute probabilities from theoretical distributions. It is widely available on VAX VMS mainframe systems as well as the IBM-PC and many other micro computer running the MSDOS operating system.

目次

  • How to use this book
  • experiments and variables
  • DCL
  • MSDOS
  • summary statistics
  • minitab
  • relationships between variables
  • goodness of fit
  • inference with statistics
  • comparing means
  • two experimental designs
  • multiple and stepwise regression
  • putting it all together - analysis of covariance.

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