000 03850nam a22005415i 4500
001 978-3-319-46162-5
003 DE-He213
005 20181204134230.0
007 cr nn 008mamaa
008 170127s2016 gw | s |||| 0|eng d
020 _a9783319461625
_9978-3-319-46162-5
024 7 _a10.1007/978-3-319-46162-5
_2doi
040 _aISI Library, Kolkata
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
082 0 4 _a519.5
_223
100 1 _aHeumann, Christian.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aIntroduction to Statistics and Data Analysis
_h[electronic resource] :
_bWith Exercises, Solutions and Applications in R /
_cby Christian Heumann, Michael Schomaker, Shalabh.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXIII, 456 p. 89 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPart 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 _aThis 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.
650 0 _aMathematical statistics.
650 0 _aStatistics.
650 0 _aEconometrics.
650 0 _aMacroeconomics.
650 1 4 _aStatistical Theory and Methods.
_0http://scigraph.springernature.com/things/product-market-codes/S11001
650 2 4 _aStatistics for Business/Economics/Mathematical Finance/Insurance.
_0http://scigraph.springernature.com/things/product-market-codes/S17010
650 2 4 _aEconometrics.
_0http://scigraph.springernature.com/things/product-market-codes/W29010
650 2 4 _aMacroeconomics/Monetary Economics//Financial Economics.
_0http://scigraph.springernature.com/things/product-market-codes/W32000
700 1 _aSchomaker, Michael.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aShalabh.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319461601
776 0 8 _iPrinted edition:
_z9783319461618
776 0 8 _iPrinted edition:
_z9783319834566
856 4 0 _uhttps://doi.org/10.1007/978-3-319-46162-5
912 _aZDB-2-SMA
942 _cEB
950 _aMathematics and Statistics (Springer-11649)
999 _c426615
_d426615