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Japan
John L (John Lawson) 1850 Stoddard
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R804
Discovery Miles 8 040
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Ships in 12 - 17 working days
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This book (hardcover) is part of the TREDITION CLASSICS. It
contains classical literature works from over two thousand years.
Most of these titles have been out of print and off the bookstore
shelves for decades. The book series is intended to preserve the
cultural legacy and to promote the timeless works of classical
literature. Readers of a TREDITION CLASSICS book support the
mission to save many of the amazing works of world literature from
oblivion. With this series, tredition intends to make thousands of
international literature classics available in printed format again
- worldwide.
Originally published in 1973, this book describes the medieval
origins of the British education system, and the transformations
successive historical events - such as the Reformation, the Civil
War and the Industrial Revolution - have wrought on it. It examines
the effect on the educational pattern of such major cultural
upheavals as the Renaissance; it looks at the different parts
played by church and state, and the influence of new social and
educational philosophies.
An Introduction to Acceptance Sampling and SPC with R is an
introduction to statistical methods used in monitoring, controlling
and improving quality. Topics covered include acceptance sampling;
Shewhart control charts for Phase I studies; graphical and
statistical tools for discovering and eliminating the cause of
out-of-control-conditions; Cusum and EWMA control charts for Phase
II process monitoring; and the design and analysis of experiments
for process troubleshooting and discovering ways to improve process
output. Origins of statistical quality control and the technical
topics presented in the remainder of the book are those recommended
in the ANSI/ASQ/ISO guidelines and standards for industry. The
final chapter ties everything together by discussing modern
management philosophies that encourage the use of the technical
methods presented earlier. In the modern world sampling plans and
the statistical calculations used in statistical quality control
are done with the help of computers. As an open source high-level
programming language with flexible graphical output options, R runs
on Windows, Mac and Linux operating systems, and has add-on
packages that equal or exceed the capability of commercial software
for statistical methods used in quality control. In this book, we
will focus on several R packages. In addition to demonstrating how
to use R for acceptance sampling and control charts, this book will
concentrate on how the use of these specific tools can lead to
quality improvements both within a company and within their
supplier companies. This would be a suitable book for a
one-semester undergraduate course emphasizing statistical quality
control for engineering majors (such as manufacturing engineering
or industrial engineering), or a supplemental text for a graduate
engineering course that included quality control topics.
An Introduction to Acceptance Sampling and SPC with R is an
introduction to statistical methods used in monitoring, controlling
and improving quality. Topics covered include acceptance sampling;
Shewhart control charts for Phase I studies; graphical and
statistical tools for discovering and eliminating the cause of
out-of-control-conditions; Cusum and EWMA control charts for Phase
II process monitoring; and the design and analysis of experiments
for process troubleshooting and discovering ways to improve process
output. Origins of statistical quality control and the technical
topics presented in the remainder of the book are those recommended
in the ANSI/ASQ/ISO guidelines and standards for industry. The
final chapter ties everything together by discussing modern
management philosophies that encourage the use of the technical
methods presented earlier. In the modern world sampling plans and
the statistical calculations used in statistical quality control
are done with the help of computers. As an open source high-level
programming language with flexible graphical output options, R runs
on Windows, Mac and Linux operating systems, and has add-on
packages that equal or exceed the capability of commercial software
for statistical methods used in quality control. In this book, we
will focus on several R packages. In addition to demonstrating how
to use R for acceptance sampling and control charts, this book will
concentrate on how the use of these specific tools can lead to
quality improvements both within a company and within their
supplier companies. This would be a suitable book for a
one-semester undergraduate course emphasizing statistical quality
control for engineering majors (such as manufacturing engineering
or industrial engineering), or a supplemental text for a graduate
engineering course that included quality control topics.
Every technical investigation involving trial-and-error
experimentation embodies a strategy for deciding what experiments
to perform, when to quit, and how to interpret the data. This
handbook presents several statistically derived strategies which
are more efficient than any intuitive approach and will get the
investigator to their goal with the fewest experiments, give the
greatest degree of reliability to their conclusions, and keep the
risk of overlooking something of practical importance to a minimum.
Features: Provides a comprehensive desk reference on experimental
design that will be useful to practitioners without extensive
statistical knowledge Features a review of the necessary
statistical prerequisites Presents a set of tables that allow
readers to quickly access various experimental designs Includes a
roadmap for where and when to use various experimental design
strategies Shows compelling examples of each method discussed
Illustrates how to reproduce results using several popular software
packages on a supplementary website Following the outlines and
examples in this book should quickly allow a working professional
or student to select the appropriate experimental design for a
research problem at hand, follow the design to conduct the
experiments, and analyze and interpret the resulting data. John
Lawson and John Erjavec have a combined 25 years of industrial
experience and over 40 years of academic experience. They have
taught this material to numerous practicing engineers and
scientists as well as undergraduate and graduate students.
Originally published in 1973, this book describes the medieval
origins of the British education system, and the transformations
successive historical events such as the Reformation, the Civil War
and the Industrial Revolution have wrought on it. It examines the
effect on the educational pattern of such major cultural upheavals
as the Renaissance; it looks at the different parts played by
church and state, and the influence of new social and educational
philosophies. "
Originally published in 1967, this volume provides an account of
the early development of English education. The schools and
universities of the mediaeval period arose to meet the social needs
of that time. The book charts developments up to the sixteenth
century when the Reformation brought profound social and religious
changes which affected education: not only the organisation of
schools and universities but also the curriculum. This was the
turning point when the foundations of an educational system, in the
modern sense of the term, were laid.
A culmination of the author's many years of consulting and
teaching, Design and Analysis of Experiments with SAS provides
practical guidance on the computer analysis of experimental data.
It connects the objectives of research to the type of experimental
design required, describes the actual process of creating the
design and collecting the data, shows how to perform the proper
analysis of the data, and illustrates the interpretation of
results.
Drawing on a variety of application areas, from pharmaceuticals
to machinery, the book presents numerous examples of experiments
and exercises that enable students to perform their own
experiments. Harnessing the capabilities of SAS 9.2, it includes
examples of SAS data step programming and IML, along with
procedures from SAS Stat, SAS QC, and SAS OR. The text also shows
how to display experimental results graphically using SAS ODS
graphics. The author emphasizes how the sample size, the assignment
of experimental units to combinations of treatment factor levels
(error control), and the selection of treatment factor combinations
(treatment design) affect the resulting variance and bias of
estimates as well as the validity of conclusions.
This textbook covers both classical ideas in experimental design
and the latest research topics. It clearly discusses the objectives
of a research project that lead to an appropriate design choice,
the practical aspects of creating a design and performing
experiments, and the interpretation of the results of computer data
analysis. SAS code and ancillaries are available at http:
//lawson.mooo.com
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