本书主要包括抽样及描述性统计、概率、误差的传播、常用的分布、置信区间估计、假设检验、相关性和简单线性回归、多次回归、析因实验、统计上的质量控制、变量的控制图表、计数值管制图表、单因素实验中的成对比较、利用仿真构造置信区间、预测区间和公差区间、总体均值的大样本置信区间等内容。

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.