Statistics

Statistics : Concepts and Applications Workbook

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Description

Statistics: Concepts and Applications is a 'classical' general statistics text written in modern voice. The authors bring mathematical, theoretical and conceptual integrity to a body of topics and techniques that is appropriate to a first course in statistics and do so in a way that is accessible to students whose mathematical preparation does not go beyond the standard curriculum for college algebra. The informal, conversational prose delivers conceptual richness and advances a quiet subtext of mathematics instruction that achieves a high level of mathematical rigour. The text presents a thorough, step-by-step development of fundamental principles. Statistics: Concepts and Applications is backed by a package of ancillary materials: an instructor's manual with full solutions to exercises, rather than just answers, and an inexpensive supplementary workbook and tutorial ('User-Friendly') with remarkably powerful and easy-to-use DOS-compatible computer software package (ASP).show more

Product details

  • Online resource
  • Cambridge University Press (Virtual Publishing)
  • Cambridge, United Kingdom
  • English
  • 104 b/w illus.
  • 1139174142
  • 9781139174145

Review quote

"The authors write in lively, engaging prose that is mathematically rigorous and pedagogically sound." Contemporary Psychologyshow more

Table of contents

1. The organization of data; 2. Describing distributions; 3. Describing individuals in distributions; 4. Describing joint distributions of data; 5. Introduction to probability; 6. Discrete probability distributions; 7. Continuous probability distributions; 8. Sampling distributions and estimation; 9. Hypothesis testing; 10. Testing hypotheses about population means; 11. Testing hypotheses about population variances; 12. Testing hypotheses about several population means mu1, mu2,..., muj: analysis of variance; 13. More complex analysis of variance; 14. Testing hypotheses about correlation and regression; 15. Testing hypotheses about entire distributions: Pearson's chi-square.show more

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