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Introduction to Statistics and Data Analysis : With Exercises, Solutions and Applications in R / by Christian Heumann, Michael Schomaker, Shalabh

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Cham : Springer International Publishing, 2022Publisher: Cham : Imprint: Springer, 2022Edition: 2nd ed. 2022Description: 1 Online-Ressource(XVII, 584 p. 118 illus., 6 illus. in color.)ISBN:
  • 9783031118333
Subject(s): Additional physical formats: 9783031118326 | 9783031118340 | 9783031120251 | Erscheint auch als: 9783031118326 Druck-Ausgabe | Erscheint auch als: 9783031118340 Druck-Ausgabe | Erscheint auch als: 9783031120251 Druck-AusgabeDDC classification:
  • 519.5 23
DOI: DOI: 10.1007/978-3-031-11833-3Online resources: Summary: Part 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 -- Logistic Regression -- Part IV Additional Topics Simple Random Sampling and Bootstrapping -- Causality -- Part V Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries.Summary: 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.PPN: PPN: 1833431707Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS
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