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SSRN Electronic Journal
Article . 2005 . Peer-reviewed
Data sources: Crossref
EconStor
Research . 2005
Data sources: EconStor
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Integrable E-Lements for Statistics Education

Authors: Wolfgang Härdle; Sigbert Klinke; Uwe Ziegenhagen;

Integrable E-Lements for Statistics Education

Abstract

Without doubt modern education in statistics must involve practical, computer-based data analysis but the question arises whether and how computational elements should be integrated into the canon of methodological education. Should the student see and study high-level programming code right at the beginning of his or her studies? Which technology can be presented during class and which computational elements can re-occur (at increasing level of complexity) during the different courses? In this paper we address these questions and discuss where e-techniques have their limits in statistics education.

Country
Germany
Keywords

electronic books, hypertext, e-supported teaching, statistical software, electronic books, ddc:330, 330 Wirtschaft, C19, e-supported teaching, 17 Wirtschaft, statistical software, I21, hypertext, jel: jel:C19, jel: jel:I21

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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