Statistics with JMP: Hypothesis Tests, ANOVA and Regression

Regular price €73.99

Statistics methodology

A01=David Meintrup
A01=Peter Goos
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Age Group_Uncategorized
ANOVA
Author_David Meintrup
Author_Peter Goos
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Category1=Non-Fiction
Category=PBT
Category=UFM
COP=United States
Delivery_Delivery within 10-20 working days
engineering

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eq_computing
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eq_non-fiction
Hypothesis Tests
JMP
Language_English
non-parametric tests
p-values
PA=Available
parameter estimation
parametric hypothesis tests
point estimates and confidence interval estimates
Price_€50 to €100
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Regression
simple linear regression
softlaunch

Product details

  • ISBN 9781119097150
  • Weight: 1111g
  • Dimensions: 178 x 246mm
  • Publication Date: 12 Apr 2016
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
  • Language: English
Delivery/Collection within 10-20 working days

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Statistics with JMP: Hypothesis Tests, ANOVA and Regression

 Peter Goos, University of Leuven and University of Antwerp, Belgium

 David Meintrup, University of Applied Sciences Ingolstadt, Germany

 A first course on basic statistical methodology using JMP

This book provides a first course on parameter estimation (point estimates and confidence interval estimates), hypothesis testing, ANOVA and simple linear regression. The authors approach combines mathematical depth with numerous examples and demonstrations using the JMP software.

Key features:

  • Provides a comprehensive and rigorous presentation of introductory statistics that has been extensively classroom tested.
  • Pays attention to the usual parametric hypothesis tests as well as to non-parametric tests (including the calculation of exact p-values).
  • Discusses the power of various statistical tests, along with examples in JMP to enable in-sight into this difficult topic.
  • Promotes the use of graphs and confidence intervals in addition to p-values.
  • Course materials and tutorials for teaching are available on the book's companion website.

Masters and advanced students in applied statistics, industrial engineering, business engineering, civil engineering and bio-science engineering will find this book beneficial. It also provides a useful resource for teachers of statistics particularly in the area of engineering.

Peter Goos, Department of Mathematics, Statistics and Actuarial Sciences, Faculty of Applied Economics of the University of Antwerp, Belgium.

David?Meintrup, Department of Mathematics, Statistics and Actuarial Sciences, Faculty of Applied Economics of the University of Antwerp, Belgium.