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Introduction to Statistics
and Data Analysis
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with exercises, solutions and
applications in R -
by Christian Heumann, Michael Schomaker
and Shalabh
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This introductory statistics textbook is
available from Springer here.
The book conveys the essential concepts and
tools needed to develop and nurture statistical
thinking. It presents descriptive, inductive and
explorative statistical methods and guides the
reader through the process of quantitative data
analysis. Data analysis has become an integral
part of scientific studies, including experimental
sciences and interdisciplinary research. Issues
such as judging the credibility of data,
analyzing the data, evaluating the reliability
of the obtained results and finally drawing the
correct and appropriate conclusions from the
results are vital. The text is primarily intended
for undergraduate students and self-learners
in disciplines like business administration,
the social sciences, medicine, politics,
psychology and others. It features a wealth of
examples, exercises and solutions with
computer code in the statistical programming
language R as well as supplementary material
that will enable the reader to quickly adapt
all methods to their own applications. A list
of errata and corrections can be downloaded here
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Solutions to
R-Exercises
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Datasets
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Solutions to
Chapter 1
Solutions to Chapter 2
Solutions to Chapter 3
Solutions to Chapter 4
Solutions to Chapter 7
Solutions to Chapter 8
Solutions to Chapter 9
Solutions to Chapter 10
Solutions to Chapter 11
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Pizza
Delivery Data
Decathlon Data
Theatre Data
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Prof. Heumann is
a professor at the Ludwig-Maximilian-Universität
München, Germany, where he teaches students in
Bachelor and Master programs offered by the
Department of Statistics, as well as
undergraduate students in the Bachelor of
Science programs in business administration and
economics. His research interests include
statistical modeling, computational statistics
and all aspects of missing data. |
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Dr. Schomaker is
a Senior Researcher and Biostatistician at the
Centre For Infectious Disease Epidemiology
& Research (CIDER), University of Cape Town,
South Africa. He received his doctoral degree
from the University of Munich. He has taught
undergraduate students from the business and
medical sciences for many years and has written
contributions for various introductory
textbooks. His research chiefly focuses on
missing data, causal inference, model averaging
and HIV/AIDS. |
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Prof. Shalabh is
a Professor at the Indian Institute of
Technology Kanpur, India. He received his Ph.D.
from the University of Lucknow (India) and
completed his post-doctoral work at the
University of Pittsburgh (USA) and University of
Munich (Germany). He has over twenty years
experience in teaching and research. His main
research areas are linear models, regression
analysis, econometrics, measurement error
models, missing data models and sampling theory. |
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For
feedback, or reporting errors, please write an
email to:
christian.heumann _@_
stat.uni-muenchen.de
michael.schomaker _@_ uct.ac.za
shalab _@_ iitk.ac.in |
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