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The sixth edition of this book continues to demonstrate how to apply probability theory to gain insight into real, everyday statistical problems and situations.
As in the previous editions, carefully developed coverage of probability motivates probabilistic models of real phenomena and the statistical procedures
that follow. This approach ultimately results in an intuitive understanding of
statistical procedures and strategies most often used by practicing engineers
and scientists.
This book has been written for an introductory course in statistics or in probability and statistics for students in engineering, computer science, mathematics,
statistics, and the natural sciences. As such it assumes knowledge of elementary
calculus.
Organization and coverage
Chapter 1 presents a brief introduction to statistics, presenting its two branches
of descriptive and inferential statistics, and a short history of the subject and
some of the people whose early work provided a foundation for work done
today.
The subject matter of descriptive statistics is then considered in Chapter 2.
Graphs and tables that describe a data set are presented in this chapter, as are
quantities that are used to summarize certain of the key properties of the data
set.
To be able to draw conclusions from data, it is necessary to have an understanding of the data’s origination. For instance, it is often assumed that the
data constitute a “random sample” from some population. To understand exactly what this means and what its consequences are for relating properties of
the sample data to properties of the entire population, it is necessary to have
some understanding of probability, and that is the subject of Ch |
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