Principles of Statistics for Engineers and Scientists, 2/e (IE-Paperback)

Principles of Statistics for Engineers and Scientists, 2/e (IE-Paperback)

作者: William Navidi
出版社: McGraw-Hill Education
出版在: 2020-01-01
ISBN-13: 9781260570731
ISBN-10: 1260570738
總頁數: 620 頁





內容描述


Description
Principles of Statistics for Engineers and Scientists, Second Edition, emphasizes statistical methods and how they are applied to problems in science and engineering. This text contains many examples that feature real, contemporary data sets, both to motivate students and to demonstrate connections to industry and scientific research. Because statistical analyses are done on computers, the book contains exercises and examples that involve interpreting, as well as generating, computer output. This book may be used effectively with any software package.
New to This Edition
More than 250 new exercises have been added to offer a wider variety of exercises for practice.
Resistance to outliers content has been added to Chapter 1 to aid in understanding the differences between means and medians.
Material on interpreting the slope of the least-squares line is now included in Chapter 2 as it is important to understand interpretation of results from linear regression.
F-test for variance has been added to Chapter 7 because it is a frequently used method.
Features
Linear models are introduced in Chapter 2 to give instructors the option of covering this important topic early.
Many exercises involve interpreting computer output, giving students practice in this essential skill.
Many examples and exercises use real data from scientific articles, which allow students to see real-world applications of the concepts and methods they are learning.
Procedures for checking assumptions and selecting models are emphasized in the coverage of linear regression.


目錄大綱


Table of Contents
1 Summarizing Univariate Data
2 Summarizing Bivariate Data
3 Probability
4 Commonly Used Distributions
5 Point and Interval Estimation for a Single Sample
6 Hypothesis Tests for a Single Sample
7 Inferences for Two Samples
8 Inference in Linear Models
9 Factorial Experiments
10 Statistical Quality Control




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