Applied Statistics for Engineers and Scientists: Using Microsoft Excel & Minitab

Levine, David; Ramsey, Patricia; Smidt, Robert

ISBN 10: 0134888014 / ISBN 13: 9780134888019

Published by Pearson, 2000

About this Item

The book is in good condition with all pages and cover intact, including the dust jacket if originally issued. The spine may show light wear. Pages may contain some notes or highlighting, and there might be a "From the library of" label. Boxed set packaging, shrink wrap, or included media like CDs may be missing.

Seller Inventory # BSM.16NOJ

Bibliographic Details

• Title: Applied Statistics for Engineers and Scientists: Using Microsoft Excel & Minitab
• Publisher: Pearson
• Publication Date: 2000
• Language: English
• ISBN 10: 0134888014
• ISBN 13: 9780134888019
• Binding: Soft cover
• Condition: good

About this title

Synopsis

For courses in Probability and Statistics.

This applied text for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important to students in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software (Microsoft Excel and Minitab) as well as in-depth coverage of quality and experimental design complete this treatment of statistics.

From the Back Cover

This applied book for engineers and scientists, written in a non-theoretical manner, focuses on underlying principles that are important in a wide range of disciplines. It emphasizes the interpretation of results, the presentation and evaluation of assumptions, and the discussion of what should be done if the assumptions are violated. Integration of spreadsheet and statistical software complete this treatment of statistics. Chapter topics include describing and summarizing data; probability and discrete probability distributions; continuous probability distributions and sampling distributions; process control charts; estimation procedures; hypothesis testing; the design of experiments; and simple linear and multiple regression models. For individuals interested in learning statistics—without a high level of mathematical sophistication.