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03249nam a22004815i 4500 |
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978-3-319-46162-5 |
| 003 |
DE-He213 |
| 005 |
20170127040741.0 |
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cr nn 008mamaa |
| 008 |
170127s2016 gw | s |||| 0|eng d |
| 020 |
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|a 9783319461625
|9 978-3-319-46162-5
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|a 10.1007/978-3-319-46162-5
|2 doi
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|d GrThAP
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|a QA276-280
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|a PBT
|2 bicssc
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|a MAT029000
|2 bisacsh
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|a 519.5
|2 23
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| 100 |
1 |
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|a Heumann, Christian.
|e author.
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| 245 |
1 |
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|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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| 264 |
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2016.
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| 300 |
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|a XIII, 456 p. 89 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 347 |
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|a text file
|b PDF
|2 rda
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|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.
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|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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| 650 |
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0 |
|a Statistics.
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| 650 |
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0 |
|a Econometrics.
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| 650 |
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0 |
|a Macroeconomics.
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| 650 |
1 |
4 |
|a Statistics.
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| 650 |
2 |
4 |
|a Statistical Theory and Methods.
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| 650 |
2 |
4 |
|a Statistics for Business/Economics/Mathematical Finance/Insurance.
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| 650 |
2 |
4 |
|a Econometrics.
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| 650 |
2 |
4 |
|a Macroeconomics/Monetary Economics//Financial Economics.
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| 700 |
1 |
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|a Schomaker, Michael.
|e author.
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| 700 |
1 |
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|a Shalabh.
|e author.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
0 |
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|t Springer eBooks
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| 776 |
0 |
8 |
|i Printed edition:
|z 9783319461601
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| 856 |
4 |
0 |
|u http://dx.doi.org/10.1007/978-3-319-46162-5
|z Full Text via HEAL-Link
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| 912 |
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|a ZDB-2-SMA
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| 950 |
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|a Mathematics and Statistics (Springer-11649)
|
