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| Hauptverfasser: | , |
|---|---|
| Format: | Recurso educativo Open Access |
| Sprache: | en |
| Veröffentlicht: |
1986
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| Schlagworte: | |
| Online-Zugang: | https://eric.ed.gov/?id=EJ344291 |
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| _version_ | 1867180827176075264 |
|---|---|
| author | Bookstein, Abraham Podet, Eve B. |
| author_facet | Bookstein, Abraham Podet, Eve B. Bookstein, Abraham Podet, Eve B. |
| collection | Education Resources Information Center |
| contents | Predicting Graduate Library School Performance Using a Probabilistic Retrieval Model. Bookstein, Abraham Podet, Eve B. Academic Achievement Grade Point Average Graduate Students Higher Education Information Retrieval Library Education Predictive Measurement Predictive Validity Probability Regression (Statistics) Statistical Analysis Statistical Inference Three versions of a probabilistic model adapted from the theory of information retrieval--a binary version, a version using the full value of the data, and a version using principal components--were tested and applied to data available from application forms to predict graduate school performance of library school students. (EM) |
| format | Recurso educativo Open Access |
| id | eric_EJ344291 |
| institution | ERIC Institute of Education Sciences |
| language | en |
| publishDate | 1986 |
| record_format | eric |
| spellingShingle | Predicting Graduate Library School Performance Using a Probabilistic Retrieval Model. Bookstein, Abraham Podet, Eve B. Academic Achievement Grade Point Average Graduate Students Higher Education Information Retrieval Library Education Predictive Measurement Predictive Validity Probability Regression (Statistics) Statistical Analysis Statistical Inference Predicting Graduate Library School Performance Using a Probabilistic Retrieval Model. Bookstein, Abraham Podet, Eve B. Academic Achievement Grade Point Average Graduate Students Higher Education Information Retrieval Library Education Predictive Measurement Predictive Validity Probability Regression (Statistics) Statistical Analysis Statistical Inference Three versions of a probabilistic model adapted from the theory of information retrieval--a binary version, a version using the full value of the data, and a version using principal components--were tested and applied to data available from application forms to predict graduate school performance of library school students. (EM) |
| title | Predicting Graduate Library School Performance Using a Probabilistic Retrieval Model. |
| topic | Academic Achievement Grade Point Average Graduate Students Higher Education Information Retrieval Library Education Predictive Measurement Predictive Validity Probability Regression (Statistics) Statistical Analysis Statistical Inference |
| url | https://eric.ed.gov/?id=EJ344291 |