Amazon cover image
Image from Amazon.com

Statistics with JMP : hypothesis tests, ANOVA, and regression Peter Goos, David Meintrup

By: Contributor(s): Material type: TextTextPublication details: xix, 624 p. : Wiley, c2016.Description: xvii, 624 p. : ill. ; 26 cmISBN:
  • 9781119097150
  • 1119097150
Subject(s): DDC classification:
  • 519.5028553 GO ST
Online resources: Summary: 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.
Star ratings
    Average rating: 0.0 (0 votes)
Holdings
Item type Current library Call number Status Date due Barcode
REGULAR University of Wollongong in Dubai Main Collection 519.5028553 GO ST (Browse shelf(Opens below)) Available T0058713

Includes bibliographical references and index.

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.

There are no comments on this title.

to post a comment.