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https://nccur.lib.nccu.edu.tw/handle/140.119/104486
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Title: | 國家發展指標之探索--以教育與經濟發展指標為主 |
Other Titles: | Exploration on the Indicators of National Development: With Emphasis on Indicators of Educational and Economic Development |
Authors: | 馬信行 Ma, Hsen-Hsing |
Contributors: | 教育系 |
Date: | 1988-12 |
Issue Date: | 2016-12-05 14:56:07 (UTC+8) |
Abstract: | 為尋找國家發展的指標,本研究使用世界銀行的統計資料,以九個變項:GNP,預期壽命,農業勞動率,都市人口率,每位醫生服務人口,生育率、小學在學率、中學在學率,及大學在學率,作群集分析。將102個國家分為四類,計先進國家13國,半先進國家23國,部分開發國家28國,欠開發國家38國。為檢定群集分析分類的適宜性,再用區別分析將群集分類後的國家重新分類,結果正確分類率為90.2%。中華民國臺灣被分類為半先進國家,如用區別分數標出在領域圖的位置,則臺灣落在半先進國家與先進國家的邊界上。本研究也針對臺灣目前在發展階段中所遭到的問題提出解決建議。本研究另一目的是要了解教育發展與經濟發展之關係。因此用GNP當依變項,其餘八個指標當自變項求迴歸方程。結果發現在考慮線性重合之問題後,各自變項對GNP皆有顯著影響(P<.0001)。 The chief purpose of this study is to search the representative indicators of national development. Nine indicators were used in the Cluster Analysis, which clusters 102 sample countries into four groups: advanced,semi-advanced, partial developed, and underdeveloped countries. The raw data are adapted from the World Bank report 1987 and the nine indicators used are GNP, life expectancy at birth, percentage of labor force in agriculture, urban population as percentage of total population, population per physician, total ferility rate, number enrolled in primary school, secondary school, and higher education as percentage of each age group. In order to examine the suitability of clustering, Discriminant Analysis was employed to reclassify the clustered countries. 90.2% of countries were correctly reclassified. The ROC, Taiwan is classified as a semi-advanced country as done by Harbison & Myers in 1964. According to the discriminant scores, Taiwan is located at the borderline between semi-advanced and advanced country group in the territorial map. Solutions to the problems confronted by Taiwan as a semi-advanced country are suggested. The another purpose of this study is to find the relationship between educational development and economic develpment. In a regression equation the GNP was used as criterion and the other eight variables as predictors. After considering the multicollinearity, the results showed that each independent variable has significant influence on GNP (p<.0001). |
Relation: | 國立政治大學學報, 58,229-271 |
Data Type: | article |
Appears in Collections: | [第58期] 期刊論文
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58-229-271.pdf | | 3875Kb | Adobe PDF2 | 583 | View/Open |
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