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Since the beginning of the seventies computer hardware is available
to use programmable computers for various tasks. During the
nineties the hardware has developed from the big main frames to
personal workstations. Nowadays it is not only the hardware which
is much more powerful, but workstations can do much more work than
a main frame, compared to the seventies. In parallel we find a
specialization in the software. Languages like COBOL for business
orientated programming or Fortran for scientific computing only
marked the beginning. The introduction of personal computers in the
eighties gave new impulses for even further development, already at
the beginning of the seven ties some special languages like SAS or
SPSS were available for statisticians. Now that personal computers
have become very popular the number of pro grams start to explode.
Today we will find a wide variety of programs for almost any
statistical purpose (Koch & Haag 1995)."
This book describes an interactive statistical computing
environment called 1 XploRe. As the name suggests, support for
exploratory statistical analysis is given by a variety of
computational tools. XploRe is a matrix-oriented statistical
language with a comprehensive set of basic statistical operations
that provides highly interactive graphics, as well as a programming
environ ment for user-written macros; it offers hard-wired
smoothing procedures for effective high-dimensional data analysis.
Its highly dynamic graphic capa bilities make it possible to
construct student-level front ends for teaching basic elements of
statistics. Hot keys make it an easy-to-use computing environment
for statistical analysis. The primary objective of this book is to
show how the XploRe system can be used as an effective computing
environment for a large number of statistical tasks. The computing
tasks we consider range from basic data matrix manipulations to
interactive customizing of graphs and dynamic fit ting of
high-dimensional statistical models. The XploRe language is similar
to other statistical languages and offers an interactive help
system that can be extended to user-written algorithms. The
language is intuitive and read ers with access to other systems
can, without major difficulty, reproduce the examples presented
here and use them as a basis for further investigation.
This book covers all the topics found in introductory descriptive
statistics courses, including simple linear regression and time
series analysis, the fundamentals of inferential statistics
(probability theory, random sampling and estimation theory), and
inferential statistics itself (confidence intervals, testing). Each
chapter starts with the necessary theoretical background, which is
followed by a variety of examples. The core examples are based on
the content of the respective chapter, while the advanced examples,
designed to deepen students' knowledge, also draw on information
and material from previous chapters. The enhanced online version
helps students grasp the complexity and the practical relevance of
statistical analysis through interactive examples and is suitable
for undergraduate and graduate students taking their first
statistics courses, as well as for undergraduate students in
non-mathematical fields, e.g. economics, the social sciences etc.
This book describes an interactive statistical computing
environment called 1 XploRe. As the name suggests, support for
exploratory statistical analysis is given by a variety of
computational tools. XploRe is a matrix-oriented statistical
language with a comprehensive set of basic statistical operations
that provides highly interactive graphics, as well as a programming
environ ment for user-written macros; it offers hard-wired
smoothing procedures for effective high-dimensional data analysis.
Its highly dynamic graphic capa bilities make it possible to
construct student-level front ends for teaching basic elements of
statistics. Hot keys make it an easy-to-use computing environment
for statistical analysis. The primary objective of this book is to
show how the XploRe system can be used as an effective computing
environment for a large number of statistical tasks. The computing
tasks we consider range from basic data matrix manipulations to
interactive customizing of graphs and dynamic fit ting of
high-dimensional statistical models. The XploRe language is similar
to other statistical languages and offers an interactive help
system that can be extended to user-written algorithms. The
language is intuitive and read ers with access to other systems
can, without major difficulty, reproduce the examples presented
here and use them as a basis for further investigation.
This book covers all the topics found in introductory descriptive
statistics courses, including simple linear regression and time
series analysis, the fundamentals of inferential statistics
(probability theory, random sampling and estimation theory), and
inferential statistics itself (confidence intervals, testing). Each
chapter starts with the necessary theoretical background, which is
followed by a variety of examples. The core examples are based on
the content of the respective chapter, while the advanced examples,
designed to deepen students' knowledge, also draw on information
and material from previous chapters. The enhanced online version
helps students grasp the complexity and the practical relevance of
statistical analysis through interactive examples and is suitable
for undergraduate and graduate students taking their first
statistics courses, as well as for undergraduate students in
non-mathematical fields, e.g. economics, the social sciences etc.
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