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OverviewThis 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. Full Product DetailsAuthor: Christian Heumann , Michael Schomaker , ShalabhPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: Softcover reprint of the original 1st ed. 2016 Dimensions: Width: 15.50cm , Height: 2.40cm , Length: 23.50cm Weight: 0.718kg ISBN: 9783319834566ISBN 10: 3319834568 Pages: 456 Publication Date: 01 September 2018 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsPart I Descriptive Statistics: Introduction and Framework.- Frequency Measures and Graphical Representation of Data.- Measures of Central Tendency and Dispersion.- Association of Two Variables.- Part I Probability Calculus: Combinatorics.- Elements of Probability Theory.- Random Variables.- Probability Distributions.- Part III Inductive Statistics: Inference.- Hypothesis Testing.- Linear Regression.- Part IV Appendices: Introduction to R.- Solutions to Exercises.- Technical Appendix.- Visual Summaries.ReviewsAuthor InformationDr. Christian Heumann is a professor at the Ludwig-Maximilian-Universität Munich, 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. Dr. Michael 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. Dr. 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, error-measurement models, missing data models and sampling theory. Tab Content 6Author Website:Countries AvailableAll regions |
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