# 工程統計

## Miller & Freund`s Probability & Statistics for Engineers 9/e

+作者：

### Johnson

+年份：
2017 年9 版
+ISBN：
9781292176017
+書號：
PS0452PC
+規格：

+頁數：
552
+出版商：
Pearson(Asia)

\$

●Many new examples on important current engineering and scientific data further strengthen the text’s orientation towards an applications-based introduction to statistics.
Added graphs illustrating P-values appear in several examples along with an interpretation.
More details about using R commands make it easy for students to check calculations on their own laptop or tablet, while reading an example.
Key formulas are stressed and calculation formulas are downplayed. Computation formulas are set in the context of an application which only requires all, or mostly all, integer arithmetic, and now appear only at the end of sections. Students can then check their results with their choice of software.
All examples are now numbered within each chapter.
New data-based exercises feature real applications to help stimulate interest and strengthen a student’s appreciation of the role of statistics in engineering applications.
Content highlights:
。A section on graphic presentation of 22 and 23 designs includes coverage of (i) systematically varying several input variables at a time and (ii) how to interpret interactions. This serves as a stand-alone introduction to the design of experiments for those instructors who can only devote two or three lectures to the subject.

●A clear, concise presentation helps students quickly gain an understanding of the concepts.﻿●﻿Rich problem sets give students the practice they need to learn the material.
●Do's and Don'ts at the end of each chapter help students to apply statistics correctly to avoid misuses.
●Computer exercises for MINITAB® help students learn and become familiar with this software.
●Many data sets are drawn from author Richard Johnson's own consulting activities as well as discussions with scientists and engineers about their statistical problems. This helps illustrate the statistical methods and reasoning required in order to draw generalizations from data collected in actual experiments.
●Content highlights:
。Case studies in the first two chapters illustrate the power of even simple statistical methods to suggest changes that make major improvements in production processes.﻿
。﻿Graphs of the sampling distribution show the critical region and P value, and accompany the examples of testing hypotheses. These graphs help reinforce student understanding of the critical region, significance level, and P value.﻿
。﻿Summary tables of testing procedures provide a convenient reference for students.﻿
。﻿Solid treatment of confidence interval techniques and hypothesis testing procedures, which clearly and consistently delineates the steps for hypothesis testing in each application.﻿
。﻿Clear, current coverage of two-level factorial design. To explore interactions, engineers have to know about experiments where more than one variable has been changed at the same time in design.
。A full chapter on modern ideas of quality improvement provides up-to-date coverage of this popular significant trend in the field.﻿
。﻿Accessible discussion on joint distributions and the properties of expectation--this is a difficult topic not always covered in the course, but if so desired, here is a nice, quick treatment of it.

Richard A. Johnson, University of Wisconsin-Madison
Irwin Miller
John Freund

1.Introduction
2.Organization and Deion of Data
3.Probability
4.Probability Distributions
5.Probability Densities
6.Sampling Distributions
7.Inferences Concerning a Mean
8.Comparing Two Treatments
9.Inferences Concerning Variances
10.Inferences Concerning Proportions
11.Regression Analysis
12.Analysis of Variance
13.Factorial Experimentation
14.Nonparametric Tests
15.The Statistical Content of Quality Improvement Programs
16.Application to Reliability and Life Testing