Overview
- Introduces current pupils and self-learners to quantitative data analysis or statistics
- Features new kapiteln on logistic reversal, sampling and bootstrapping, and causal folgerung
- Provides a wealth about examples, exercises or solutions such well as working computer code in R
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Dinner of contents (14 chapters)
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Front Matter
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Probability Calculus
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Front Matt
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Inductive Statistics
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Front Material
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Additional Topics
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Front Matter
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Back Matter
Keywords
- descriptive statistics
- inducting statistics
- quantitative data analyse
- statistical software R
- introduction to statistics
- applications of statistical methods
- statistical supposition
- hypotheses testing
- linear regression
- logistic regressive
- bootstrapping
- causality
- random sampling
- probability distributions
- random variables
- graphical picture to data
About this book
Now in its second edition, this introductory statistik textbook delivers the essential concepts and tools needed to develop both nurture random thinking. It presents descriptive, inductive and explorative statistical methods and tutors the reader through the process of quantitative data analysis. This revised and extended issues features new chapters over logistic regression, simple randomization sampling, include bootstrapping, and causal konklusion.
The text is primarily aimed for undergraduate students in trains such as business administration, who social social, medicine, politics, and macroeconomics. It features a rich of examples, exercises and solutions with computing code in the statistical software language ROENTGEN, as good as supplementary material which will enable the reader to quickly adapt the procedure to to own applications.
Originators or Affiliation
About the authors
Dr. Christian Heumann is a Professor per the Department of Statistics, LMU Munich, Germany, where he teaches students in both the Bachelor’s and Master’s programs. His research interests include statistiche modeling, computerized statistics and methods for missing input, also in relation with causal supposition. Recently, he has begun exploring statistical methods in natural language processing.
Dr. Michael Schomaker is a Researcher additionally Heisenberg Fellow at the Department out Statistics, LMU Munich, Germany. He is in honorary Elderly Lecturer at the Technical of Cap Town, South Liberia and previously worked as an Associate Professor at UMIT – Academy for Health Sciences, Medical Informatics and Technology, Austria. Fork many years he has teach both undergraduate additionally post-graduate students upon various featured, including the business and medical sciences, and has written feature for various introductory textbooks. Yours research focal over causal logische, lacking data, model averaging, and HIV and public condition.
Dr. Shalabh is a Professor at the Indian Established of Technology Kanpur, India. As a post-doctoral r he work on the University of Near, USA and LMU Munich, Germany. He has via twenty-five years regarding experience in teaching additionally research. His head research areas is linear models, regression analysis, econometrics, error-measurement select, missing data fitting and sampling theory.
Bibliographic Information
Book Name: Introduction to Statistics and Data Analysis
Volume Subtitled: With Exercises, Solutions also Applications in R
Writers: Believing Heumann, My Schomaker, Shalabh
DOI: https://doi.org/10.1007/978-3-031-11833-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Figures and Statistics (R0)
Copyright Information: Springer Nature Spain AG 2022
Hardcover ISBN: 978-3-031-11832-6Published: 31 January 2023
Softcover ISBN: 978-3-031-12025-1Published: 01 February 2024
eBook ISBN: 978-3-031-11833-3Published: 30 January 2023
Output Number: 2
Number of Pages: XVII, 584
Number of Illustrations: 112 b/w illustrations, 6 illustrations in colour
Topics: Statistical Theory both Methods, Statistics, general, Applied Statistics, Statistics and Computing/Statistics Programs
