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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): Material type: TextTextPublisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: 1 online resource (XIII, 456 pages 89 illustrations)Content type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9783319834566
Subject(s): LOC classification:
  • QA276 I61 2016
Contents:
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.
Summary: 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, et cetera 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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Holdings
Item type Current library Call number Copy number Status Notes Barcode
Open Shelf Albukhary International University LEVEL 2 QA276 I61 2016 (Browse shelf(Opens below)) 1/3 Available Programmes : BSD 1800003754
Red Spot Albukhary International University LEVEL 2 QA276 I61 2016 (Browse shelf(Opens below)) 2/3 Available Programmes : BSD 1800003755
Open Shelf Albukhary International University LEVEL 2 QA276 I61 2016 (Browse shelf(Opens below)) 3/3 Available Programmes : BSD 1800003756
Total holds: 0

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, et cetera 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.

Description based on publisher-supplied MARC data.

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