Table of Contents Conversion Guide: Montgomery 3rd Edition to 4th Edition
Applied Statistics &
Applied Statistics & Probability for Engineers 3rd Edition
th
Probability for Engineers 4
Edition
1-1
The Engineering Method & Statistical Thinking
1-1
The Engi
Applied Statistics and Probability for Engineers, 4th edition
Errata
December 17 2007
1st Printing
Chapter 2
Page 31, exercise 2-49, should be used in Section 2-4
Page 54, exercise 2-109, change grammar from A sample is to Sample are
Page 61, exercise 2-
Table of Contents Conversion Guide: Devore 6/e to Montgomery & Runger/ Applied Statistics, 4/e
Probability and Statistics for
Applied Statistics & Probability for Engineers, 4/e, Montgomery & Runger
Engineering and the Sciences,
6/e, Devore
1.1
Population
16-1 Quality Improvement and Statistics
Definitions of Quality
Quality means fitness for use
- quality of design
- quality of conformance
Quality is inversely proportional to
variability.
16-1 Quality Improvement and Statistics
Quality Improvement
Quality
15-1 Introduction
Most of the hypothesis-testing and confidence
interval procedures discussed in previous chapters
are based on the assumption that we are working
with random samples from normal populations.
These procedures are often called parametric
me
14-1 Introduction
An experiment is a test or series of tests.
The design of an experiment plays a major role in
the eventual solution of the problem.
In a factorial experimental design, experimental
trials (or runs) are performed at all combinations of
th
13-1 Designing Engineering Experiments
Every experiment involves a sequence of activities:
1.
2.
3.
4.
Conjecture the original hypothesis that motivates the
experiment.
Experiment the test performed to investigate the
conjecture.
Analysis the statistical
Text Illustrations
To Accompany
Montgomery/Runger Applied Stats 4e
Chapter 13. Design and Analysis of Single-Factor
Experiments: The Analysis of Variance.
f13_01
f13_02
f13_03
f13_08
f13_09
f13_10
f13_13
f13_14
p13_01
p13_02
p13_03
p13_04
p13_05
p13_07
p1
12-1 Multiple Linear Regression Models
12-1.1 Introduction
Many applications of regression analysis involve
situations in which there are more than one regressor
variable.
A regression model that contains more than one
regressor variable is called a multi
11-1 Empirical Models
Many problems in engineering and science involve
exploring the relationships between two or more
variables.
Regression analysis is a statistical technique that is very
useful for these types of problems.
For example, in a chemical pr
10-1 Introduction
10-2 Inference for a Difference in Means
of Two Normal Distributions, Variances
Known
Figure 10-1 Two independent populations.
10-2 Inference for a Difference in Means
of Two Normal Distributions, Variances
Known
Assumptions
10-2 Inferen
9-1 Hypothesis Testing
9-1.1 Statistical Hypotheses
Statistical hypothesis testing and confidence interval
estimation of parameters are the fundamental methods
used at the data analysis stage of a comparative
experiment, in which the engineer is intereste
Text Illustrations
To Accompany
Montgomery/Runger Applied Stats 4e
Chapter 9. Tests of Hypotheses for a Single Sample.
f09_01
f09_02
f09_03
f09_06
f09_07
f09_08
f09_09
f09_11
p09_93
p09_94
p09_95
p09_96
p09_97
p09_98
t09_01
t09_02
t09_03
t09_04
tun09_01
t
8-1 Introduction
In the previous chapter we illustrated how a parameter
can be estimated from sample data. However, it is
important to understand how good is the estimate
obtained.
Bounds that represent an interval of plausible values
for a parameter are
Text Illustrations
To Accompany
Montgomery/Runger Applied Stats 4e
Chapter 8. Statistical Intervals for a Single Sample.
f08_01
f08_02
f08_03
f08_04
f08_05
f08_08
f08_09
p08_30
p08_43
p08_45
p08_93
t08_01
7-1 Introduction
The field of statistical inference consists of those
methods used to make decisions or to draw conclusions
about a population.
These methods utilize the information contained in a
sample from the population in drawing conclusions.
Statist
Text Illustrations
To Accompany
Montgomery/Runger Applied Stats 4e
Chapter 7. Point Estimation of Parameters.
f07_02
f07_04
f07_05
f07_06
f07_07
f07_08
f07_09
6-1 Numerical Summaries
Definition: Sample Mean
6-1 Numerical Summaries
Example 6-1
6-1 Numerical Summaries
Figure 6-1 The sample mean as a balance point for a system of weights.
6-1 Numerical Summaries
Population Mean
For a finite population with N measu
5-1 Two Discrete Random Variables
Example 5-1
5-1 Two Discrete Random Variables
Figure 5-1 Joint probability distribution of X and Y in Example 5-1.
5-1 Two Discrete Random Variables
5-1.1 Joint Probability Distributions
5-1 Two Discrete Random Variables
4-1 Continuous Random Variables
4-2 Probability Distributions and
Probability Density Functions
Figure 4-1 Density function of a loading on a long, thin beam.
4-2 Probability Distributions and
Probability Density Functions
Figure 4-2 Probability determine