本書主要包括抽樣及描述性統(tǒng)計、概率、誤差的傳播、常用的分布、置信區(qū)間估計、假設檢驗、相關性和簡單線性回歸、多次回歸、析因實驗、統(tǒng)計上的質量控制、變量的控制圖表、計數(shù)值管制圖表、單因素實驗中的成對比較、利用仿真構造置信區(qū)間、預測區(qū)間和公差區(qū)間、總體均值的大樣本置信區(qū)間等內(nèi)容。
The idea for this book grew out of discussions between the statistics faculty and the engineering faculty at the Colorado School of Mines regarding our introductory statis-tics course for engineers. Our engineering faculty felt that the students needed sub-stantial coverage of propagation of error， as well as more emphasis on model-fitting skills. The statistics faculty believed that students needed to become more aware of some important practical statistical issues such as the checking of model assumptions and the use of simulation.
My view is that an introductory statistics text for students in engineering and sci-ence should offer all these topics in some depth. In addition， it should be flexible enough to allow for a variety of choices to be made regarding coverage， because there are many different ways to design a successful introductory statistics course. Finally，it should provide examples that present important ideas in realistic settings. Accord-ingly， the book has the following features：The book is flexible in its presentation of probability， allowing instructors wide lat-itude in choosing the depth and extent of their coverage of this topic.The book contains many examples that feature real， contemporary data sets， both to motivate students and to show connections to industry and scientific research.The book contains many examples of computer output and exercises suitable for solving with computer software.
The book provides extensive coverage of propagation of error.
The book presents a solid introduction to simulation methods and the bootstrap，including applications to verifying normality assumptions， computing probabilities，estimating bias， computing confidence intervals， and testing hypotheses.
The book provides more extensive coverage of linear model diagnostic procedures than is found in most introductory texts. This includes material on examination of residual plots， transformations of variables， and principles of variable selection in multivariate models.
The book covers the standard introductory topics， including descriptive statistics，probability， confidence intervals， hypothesis tests， linear regression， factorial experiments， and statistical quality control.
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