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|a QA278
|b .C54 2019
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|a Cleff, Thomas,
|e author.
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1 |
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|a Applied statistics and multivariate data analysis for business and economics :
|b a modern approach using SPSS, Stata, and Excel /
|c Thomas Cleff.
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| 264 |
|
1 |
|a Cham, Switzerland :
|b Springer,
|c [2019]
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|a 1 online resource
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|a text
|b txt
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|a Includes bibliographical references and index.
|
| 505 |
0 |
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|a Statistics and Empirical Research -- From Disarray to Dataset -- Univariate Data Analysis -- Bivariate Association -- Classical Measurement Theory.-Calculating Probability -- Random Variables and Probability Distributions -- Parameter Estimation -- Hypothesis Testing -- Regression Analysis -- Time Series and Indices -- Cluster Analysis -- Factor Analysis.
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| 520 |
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|a This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.
|
| 588 |
0 |
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|a Online resource; title from digital title page (viewed on August 23, 2019).
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| 650 |
|
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|a Multivariate analysis.
|0 http://id.loc.gov/authorities/subjects/sh85088390
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| 650 |
|
7 |
|a Multivariate analysis.
|2 fast
|0 (OCoLC)fst01029105
|
| 655 |
|
4 |
|a Electronic books.
|
| 776 |
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8 |
|i Print version:
|a Cleff, Thomas.
|t Applied statistics and multivariate data analysis for business and economics.
|d Cham, Switzerland : Springer, [2019]
|z 3030177661
|z 9783030177669
|w (OCoLC)1090200683
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|t Library of Congress classification
|a QA278 .C54 2019
|l Online
|c UC-FullText
|u https://link.springer.com/10.1007/978-3-030-17767-6
|z Springer Nature
|g ebooks
|i 12563057
|
