This book is the third revised and updated English edition of the German textbook \Versuchsplanung und Modellwahl" by Helge Toutenburg which was based on more than 15 years experience of lectures on the course \- sign of Experiments" at the University of Munich and interactions with the statisticians from industries and other areas of applied sciences and en- neering. This is a type of resource/ reference book which contains statistical methods used by researchers in applied areas. Because of the diverse ex- ples combined with software demonstrations it is also useful as a textbook in more advanced courses, The applications of design of experiments have seen a signi?cant growth in the last few decades in di?erent areas like industries, pharmaceutical sciences, medical sciences, engineering sciences etc. The second edition of this book received appreciation from academicians, teachers, students and applied statisticians. As a consequence, Springer-Verlag invited Helge Toutenburg to revise it and he invited Shalabh for the third edition of the book. In our experience with students, statisticians from industries and - searchers from other ?elds of experimental sciences, we realized the importance of several topics in the design of experiments which will - crease the utility of this book. Moreover we experienced that these topics are mostly explained only theoretically in most of the available books.

Statistical Analysis of Designed Experiments, Third Edition (Springer Texts in Statistics)

Business & Money

Toutenburg, Helge

Shalabh

Economics

Springer

Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R

Now in its second edition, this introductory statistics textbook 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. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. 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 the methods to their own applications.

Computers & Technology

Heumann, Christian

Schomaker, Michael

Programming

Introduction to Statistics and Data Analysis

Christian Heumann

Michael Schomaker

Springer Nature

This introductory statistics textbook 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. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. 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 in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. 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.

This introductory statistics textbook 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. In the experimental sciences and interdisciplinary research, data analysis has become an integral part of any scientific study. 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 in disciplines like business administration, the social sciences, medicine, politics, macroeconomics, etc. 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.

Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.

Linear Models and Generalizations: Least Squares and Alternatives (Springer Series in Statistics)

Rao, C.Radhakrishna

Third Edition explores the theory and applications of linear models. It presents a unified theory of inference from linear models and its generalizations with minimal assumptions, using least squares theory and alternative methods of estimation and testing.

See the best price to sell, buy, or rent books by Shalabh. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Shalabh

See the best price to sell, buy, or rent books by Shalabh. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Statistical Analysis of Designed Experiments, Third Edition (Springer Texts in Statistics)

Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R

Introduction to Statistics and Data Analysis

Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R

Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R

Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R

Introduction to Statistics and Data Analysis: With Exercises, Solutions and Applications in R

Linear Models and Generalizations: Least Squares and Alternatives (Springer Series in Statistics)

Linear Models and Generalizations: Least Squares and Alternatives (Springer Series in Statistics)