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151224s2015 sz | s |||| 0|eng d |
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|a 9783319177045
|9 978-3-319-17704-5
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|a 10.1007/978-3-319-17704-5
|2 doi
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|a QA276-280
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|a 300.727
|2 23
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|a Härdle, Wolfgang Karl.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Introduction to Statistics
|h [electronic resource] :
|b Using Interactive MM*Stat Elements /
|c by Wolfgang Karl Härdle, Sigbert Klinke, Bernd Rönz.
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250 |
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|a 1st ed. 2015.
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264 |
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2015.
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300 |
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|a XX, 516 p. 205 illus., 173 illus. in color.
|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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|a text file
|b PDF
|2 rda
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|a Basics -- One-Dimensional Frequency Distributions.- Probability Theory -- Combinatorics -- Random Variables -- Probability Distributions.- Sampling Theory.- Estimation.- Statistical Tests.- Two-dimensional Frequency Distribution.- Regression.- Time Series Analysis.
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520 |
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|a MM*Stat, together with its enhanced online version with interactive examples, offers a flexible tool that facilitates the teaching of basic statistics. It covers all the topics found in introductory descriptive statistics courses, including simple linear regression and time series analysis, the fundamentals of inferential statistics (probability theory, random sampling and estimation theory), and inferential statistics itself (confidence intervals, testing). MM*Stat is also designed to help students rework class material independently and to promote comprehension with the help of additional examples. Each chapter starts with the necessary theoretical background, which is followed by a variety of examples. The core examples are based on the content of the respective chapter, while the advanced examples, designed to deepen students' knowledge, also draw on information and material from previous chapters. The enhanced online version helps students grasp the complexity and t he practical relevance of statistical analysis through interactive examples and is suitable for undergraduate and graduate students taking their first statistics courses, as well as for undergraduate students in non-mathematical fields, e.g. economics, the social sciences etc. All R codes and data sets may be downloaded via the quantlet download center. .
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650 |
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|a Statistics .
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650 |
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|a Social sciences-Statistical methods.
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650 |
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|a Computer science-Mathematics.
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650 |
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|a Mathematical statistics.
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650 |
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|a Biometry.
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650 |
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|a Mathematical statistics-Data processing.
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650 |
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|a Statistics in Business, Management, Economics, Finance, Insurance.
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650 |
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|a Statistics in Social Sciences, Humanities, Law, Education, Behavorial Sciences, Public Policy.
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650 |
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|a Probability and Statistics in Computer Science.
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650 |
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4 |
|a Biostatistics.
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650 |
2 |
4 |
|a Statistics and Computing.
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700 |
1 |
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|a Klinke, Sigbert.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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700 |
1 |
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|a Rönz, Bernd.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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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 Nature eBook
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776 |
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|i Printed edition:
|z 9783319177038
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776 |
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|i Printed edition:
|z 9783319177052
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776 |
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|i Printed edition:
|z 9783319792378
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|u https://doi.uam.elogim.com/10.1007/978-3-319-17704-5
|z Texto Completo
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912 |
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|a ZDB-2-SMA
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912 |
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|a ZDB-2-SXMS
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950 |
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|a Mathematics and Statistics (SpringerNature-11649)
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950 |
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|a Mathematics and Statistics (R0) (SpringerNature-43713)
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