Bibliographische Detailangaben
Beteiligte: Albers, Michael J.
In: Journal of Technical Writing and Communication, 47, 2017, 2, S. 215-233
veröffentlicht:
SAGE Publications
Medientyp: Artikel, E-Artikel

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weitere Informationen
Umfang: 215-233
ISSN: 1541-3780
0047-2816
DOI: 10.1177/0047281617692067
veröffentlicht in: Journal of Technical Writing and Communication
Sprache: Englisch
Schlagwörter:
Kollektion: SAGE Publications (CrossRef)
Inhaltsangabe

<jats:p> A quantitative research study collects numerical data that must be analyzed to help draw the study’s conclusions. Teaching quantitative data analysis is not teaching number crunching, but teaching a way of critical thinking for how to analyze the data. The goal of data analysis is to reveal the underlying patterns, trends, and relationships of a study’s contextual situation. Learning data analysis is not learning how to use statistical tests to crunch numbers but is, instead, how to use those statistical tests as a tool to draw valid conclusions from the data. Three major pedagogical goals that must be taught as part of learning quantitative data analysis are the following: (a) determining what questions to ask during all phases of a data analysis, (b) recognizing how to judge the relevance of potential questions, and (c) deciding how to understand the deep-level relationships within the data. </jats:p>