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

Preface Introduction The primary questions that must be answered when a new statistics text for engineers and scientists is written relate to the issue of the contribution of the textbook to the pedagogy of teaching statistics to this audience of students and to how the text will differ from the many texts that are already available. These questions can be answered for the proposed text only in the context of recommendations that have been made as the result of a 1984 conference on the statistical education of engineers Hogg(1985) and a 1993 Quality Engineering Workshop Hogg(1994). Among the recommendations made was that engineers need to appreciate the following statistical concepts: omnipresence of variability; the use of simple graphical tools such as run charts, histograms, scatter plots, probability plots, residual plots, and control charts; basic concepts of statistical inference; the importance and essentials of carefully planned design of experiments; the philosophies of Shewhart, Deming, and other practitioners concerning the quality of products and services. The Hogg(1994) article proposed a core course of topics for engineering students. This proposed text is based on the curriculum model presented in that article. Educational Philosophy In our many years of teaching introductory statistics courses to students majoring in a wide variety of disciplines, we have continually searched for ways to improve the teaching of these courses. Over the years, our vision has come to include the following: Students need a frame of reference when learning a subject, especially one that is not their major. This frame of reference for engineering and science students should be applications to the various areas of engineering and the sciences. The discussion of each statistical topic should include references to at least one of these areas of application. Virtually all the students taking introductory statistics courses for engineers and scientists are majoring in areas other than statistics. Introductory courses should, therefore, focus on the underlying principles that are important for nonstatistics majors. The use of spreadsheet and/or statistical software should be integrated into all aspects of the introductory statistics course. The reality that exists in the workplace is that spreadsheet software (and sometimes statistical software) is typically available on one's computer desktop. Our teaching approach needs to recognize this reality and make our courses more consistent with the workplace environment. Textbooks that use software must provide detailed instructions that maximizes the student's ability to use the software with a minimum risk of failure. Instruction for each topic should focus on (1) the application of the topic to an area of engineering or the sciences, (2) the interpretation of results, (3) the presentation of assumptions, (4) the evaluation of the assumptions, and (5) the discussion of what should be done if the assumptions are violated. These 'points are particularly important in regression, forecasting and in hypothesis testing. Although the illustration of some computations is inevitable, the focus on computations should be minimized. Both classroom examples and homework exercises should relate to actual or realistic data as much as possible. Introductory courses should avoid an over-concentration on one topic area and instead provide breadth of coverage of a variety of statistical topics. This will help students avoid the "I can't see the forest for the trees" syndrome. The main features of this proposed text are summarized in the following sections. Main Feature: Emphasis on Data Analysis and Interpretation of Computer Output The personal computer revolution has dramatically changed how information is analyzed in the workplace and how stRobert K. Smidt is the author of 'Applied Statistics for Engineers and Scientists: Using Microsoft Excel & Minitab', published 2000 under ISBN 9780134888019 and ISBN 0134888014.