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Introduction to statistics and data ...

Heumann, Christian.

Introduction to statistics and data analysiswith exercises, solutions and applications in R /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Introduction to statistics and data analysisby Christian Heumann, Michael Schomaker, Shalabh.
Reminder of title:	with exercises, solutions and applications in R /
Author:	Heumann, Christian.
other author:	Schomaker, Michael.
Published:	Cham :Springer International Publishing :2016.
Description:	xiii, 456 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Mathematical statistics.
Online resource:	http://dx.doi.org/10.1007/978-3-319-46162-5
ISBN:	9783319461625$q(electronic bk.)

Introduction to statistics and data analysiswith exercises, solutions and applications in R /
Heumann, Christian.

Introduction to statistics and data analysiswith exercises, solutions and applications in R /[electronic resource] :by Christian Heumann, Michael Schomaker, Shalabh. - Cham :Springer International Publishing :2016. - xiii, 456 p. :ill., digital ;24 cm.

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 -- Part IV Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries.

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.

ISBN: 9783319461625$q(electronic bk.)

Standard No.: 10.1007/978-3-319-46162-5doiSubjects--Topical Terms:

181877
Mathematical statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Introduction to statistics and data analysiswith exercises, solutions and applications in R /
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245 1 0 $a Introduction to statistics and data analysis $h [electronic resource] : $b with exercises, solutions and applications in R / $c by Christian Heumann, Michael Schomaker, Shalabh.
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505 0 $a 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 -- Part IV Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries.
520 $a 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.
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700 1 $a Schomaker, Michael. $3 766723
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