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Statistical Hypothesis Testing with Microsoft ® Office Excel ® - Robert Hirsch - Bog

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This book provides a comprehensive treatment of the logic behind hypothesis testing. Readers will learn to understand statistical hypothesis testing and how to interpret P-values under a variety of conditions including a single hypothesis test, a collection of hypothesis tests, and tests performed on accumulating data. The author explains how a hypothesis test can be interpreted to draw conclusions, and descriptions of the logic behind frequentist (classical) and Bayesian approaches to interpret the results of a statistical hypothesis test are provided. Both approaches have their own strengths and challenges, and a special challenge presents itself when hypothesis tests are repeatedly performed on accumulating data. Possible pitfalls and methods to interpret hypothesis tests when accumulating data are also analyzed. This book will be of interest to researchers, graduate students, and anyone who has to interpret the results of statistical analyses.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783031042041
  • Indbinding:
  • Paperback
  • Sideantal:
  • 100
  • Udgivet:
  • 16. juli 2023
  • Udgave:
  • 23001
  • Størrelse:
  • 168x6x240 mm.
  • Vægt:
  • 184 g.
  • 8-11 hverdage.
  • 15. januar 2025
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Forlænget returret til d. 31. januar 2025
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Beskrivelse af Statistical Hypothesis Testing with Microsoft ® Office Excel ®

This book provides a comprehensive treatment of the logic behind hypothesis testing. Readers will learn to understand statistical hypothesis testing and how to interpret P-values under a variety of conditions including a single hypothesis test, a collection of hypothesis tests, and tests performed on accumulating data. The author explains how a hypothesis test can be interpreted to draw conclusions, and descriptions of the logic behind frequentist (classical) and Bayesian approaches to interpret the results of a statistical hypothesis test are provided. Both approaches have their own strengths and challenges, and a special challenge presents itself when hypothesis tests are repeatedly performed on accumulating data. Possible pitfalls and methods to interpret hypothesis tests when accumulating data are also analyzed. This book will be of interest to researchers, graduate students, and anyone who has to interpret the results of statistical analyses.

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