Opening Up the Black Box of Recipe Statistics: Putting the Data Back into Data Analysis.
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| Title: | Opening Up the Black Box of Recipe Statistics: Putting the Data Back into Data Analysis. |
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| Language: | English |
| Authors: | Singer, Judith D., Willett, John B. |
| Peer Reviewed: | N |
| Page Count: | 41 |
| Publication Date: | 1988 |
| Intended Audience: | Practitioners; Researchers |
| Document Type: | Opinion Papers Reference Materials - Bibliographies Speeches/Meeting Papers |
| Descriptors: | College Mathematics, Data Collection, Higher Education, Mathematical Applications, Mathematics Curriculum, Mathematics Education, Mathematics Instruction, Statistical Analysis, Statistical Data, Statistics |
| Abstract: | Statistics tend to become interesting to non-methodologists when taught in a research context that is relevant to them. Real data sets supplemented by sufficient background information can provide just such a context. Despite this, many textbook authors and instructors of applied statistics rely on artificial data sets to illustrate statistical techniques. In this paper, it is argued that artificial data sets should be eliminated from the curriculum and that they should be replaced with real data sets. Towards this end, a rationale for using real data sets and the characteristics that make data sets particularly good for instructional use are described. The difficulties encountered when using real data and strategies for compensating for these drawbacks are also discussed. Two authentic data sets and an annotated bibliography of dozens of primary and secondary data sources are included. (Author/PK) |
| Entry Date: | 1988 |
| Accession Number: | ED292684 |
| Database: | ERIC |
| Abstract: | Statistics tend to become interesting to non-methodologists when taught in a research context that is relevant to them. Real data sets supplemented by sufficient background information can provide just such a context. Despite this, many textbook authors and instructors of applied statistics rely on artificial data sets to illustrate statistical techniques. In this paper, it is argued that artificial data sets should be eliminated from the curriculum and that they should be replaced with real data sets. Towards this end, a rationale for using real data sets and the characteristics that make data sets particularly good for instructional use are described. The difficulties encountered when using real data and strategies for compensating for these drawbacks are also discussed. Two authentic data sets and an annotated bibliography of dozens of primary and secondary data sources are included. (Author/PK) |
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