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Books > Science & Mathematics > Mathematics > Probability & statistics
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Statistics for Engineering and the Sciences (Hardcover, 6th edition)
Loot Price: R2,797
Discovery Miles 27 970
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Statistics for Engineering and the Sciences (Hardcover, 6th edition)
Expected to ship within 12 - 17 working days
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Prepare Your Students for Statistical Work in the Real World
Statistics for Engineering and the Sciences, Sixth Edition is
designed for a two-semester introductory course on statistics for
students majoring in engineering or any of the physical sciences.
This popular text continues to teach students the basic concepts of
data description and statistical inference as well as the
statistical methods necessary for real-world applications. Students
will understand how to collect and analyze data and think
critically about the results. New to the Sixth Edition Many new and
updated exercises based on contemporary engineering and
scientific-related studies and real data More statistical software
printouts and corresponding instructions for use that reflect the
latest versions of the SAS, SPSS, and MINITAB software Introduction
of the case studies at the beginning of each chapter Streamlined
material on all basic sampling concepts, such as random sampling
and sample survey designs, which gives students an earlier
introduction to key sampling issues New examples on comparing
matched pairs versus independent samples, selecting the sample size
for a designed experiment, and analyzing a two-factor experiment
with quantitative factors New section on using regression residuals
to check the assumptions required in a simple linear regression
analysis The first several chapters of the book identify the
objectives of statistics, explain how to describe data, and present
the basic concepts of probability. The text then introduces the two
methods for making inferences about population parameters:
estimation with confidence intervals and hypothesis testing. The
remaining chapters extend these concepts to cover other topics
useful in analyzing engineering and scientific data, including the
analysis of categorical data, regression analysis, model building,
analysis of variance for designed experiments, nonparametric
statistics, statistical quality control, and product and system
reliability.
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