Peter Goos, Department of Statistics, University of Leuven, Faculty
of Bio-Science Engineering and University of Antwerp, Faculty of
Applied Economics, Belgium David Meintrup, Department of
Mathematics and Statistics, University of Applied Sciences
Ingolstadt, Faculty of Mechanical Engineering, Germany Thorough
presentation of introductory statistics and probability theory,
with numerous examples and applications using JMP JMP: Graphs,
Descriptive Statistics and Probability provides an accessible and
thorough overview of the most important descriptive statistics for
nominal, ordinal and quantitative data with particular attention to
graphical representations. The authors distinguish their approach
from many modern textbooks on descriptive statistics and
probability theory by offering a combination of theoretical and
mathematical depth, and clear and detailed explanations of
concepts. Throughout the book, the user-friendly, interactive
statistical software package JMP is used for calculations, the
computation of probabilities and the creation of figures. The
examples are explained in detail, and accompanied by step-by-step
instructions and screenshots. The reader will therefore develop an
understanding of both the statistical theory and its applications.
Traditional graphs such as needle charts, histograms and pie charts
are included, as well as the more modern mosaic plots, bubble plots
and heat maps. The authors discuss probability theory, particularly
discrete probability distributions and continuous probability
densities, including the binomial and Poisson distributions, and
the exponential, normal and lognormal densities. They use numerous
examples throughout to illustrate these distributions and
densities. Key features: * Introduces each concept with practical
examples and demonstrations in JMP. * Provides the statistical
theory including detailed mathematical derivations. * Presents
illustrative examples in each chapter accompanied by step-by-step
instructions and screenshots to help develop the reader s
understanding of both the statistical theory and its applications.
* A supporting website with data sets and other teaching materials.
This book is equally aimed at students in engineering, economics
and natural sciences who take classes in statistics as well as at
masters/advanced students in applied statistics and probability
theory. For teachers of applied statistics, this book provides a
rich resource of course material, examples and applications.
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