The Use of Computer-Assisted Identification of ARIMA Time-Series [microform] / Roger L. Brown.
This study was conducted to determine the effects of using various levels of tutorial statistical software for the tentative identification of nonseasonal ARIMA models, a statistical technique proposed by Box and Jenkins for the interpretation of time-series data. The Box-Jenkins approach is an iter...
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Language: | English |
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1982.
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100 | 1 | |a Brown, Roger L. | |
245 | 1 | 4 | |a The Use of Computer-Assisted Identification of ARIMA Time-Series |h [microform] / |c Roger L. Brown. |
260 | |a [S.l.] : |b Distributed by ERIC Clearinghouse, |c 1982. | ||
300 | |a 24 p. | ||
336 | |a text |2 rdacontent. | ||
337 | |a microform |2 rdamedia. | ||
338 | |a microfiche |2 rdacarrier. | ||
500 | |a ERIC Note: Paper presented at the Annual Meeting of the American Psychological Association (Washington, DC, August 1982). |5 ericd. | ||
500 | |a ERIC Document Number: ED226705. | ||
520 | |a This study was conducted to determine the effects of using various levels of tutorial statistical software for the tentative identification of nonseasonal ARIMA models, a statistical technique proposed by Box and Jenkins for the interpretation of time-series data. The Box-Jenkins approach is an iterative process encompassing several stages of development, with the initial step requiring a tentative identification which relies on two statistics, the autocorrelation function (AUCF) and the partial autocorrelation function (PACF). Both functions are calculated by the statistical software on the time-series data and supplied to the user as a correlogram. A total of 56 time-series data files were evaluated by 30 novice undergraduate students in a repeated measures procedure. Students were randomly assigned to statistical software packages which produced either AUCF and PACF correlograms (a non-tutorial package), the correlograms and access to theoretical ARIMA model correlogram examples, or correlograms and access to a decision-support tutorial. Results indicated that the use of tutorial software significantly improved the identification of ARIMA models over non-tutorial software, and the type of tutorial significantly interacted with the degree of complexity of the time-series data. The report includes 4 references, and 10 tables and figures presenting study data. (LMM) | ||
533 | |a Microfiche. |b [Washington D.C.]: |c ERIC Clearinghouse |e microfiches : positive. | ||
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650 | 1 | 7 | |a Computer Assisted Instruction. |2 ericd. |
650 | 0 | 7 | |a Computer Programs. |2 ericd. |
650 | 1 | 7 | |a Data Analysis. |2 ericd. |
650 | 0 | 7 | |a Higher Education. |2 ericd. |
650 | 1 | 7 | |a Instructional Materials. |2 ericd. |
650 | 0 | 7 | |a Mathematics Instruction. |2 ericd. |
650 | 0 | 7 | |a Models. |2 ericd. |
650 | 1 | 7 | |a Research Methodology. |2 ericd. |
650 | 0 | 7 | |a Social Psychology. |2 ericd. |
650 | 1 | 7 | |a Statistical Analysis. |2 ericd. |
650 | 0 | 7 | |a Teaching Methods. |2 ericd. |
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