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    Please use this identifier to cite or link to this item: http://ir.cnu.edu.tw/handle/310902800/765


    標題: 健康體適能測驗項目之預測模式研究
    The study of Predictive Models among the tests of Health-Related Physical
    作者: 張秀卿
    貢獻者: 休閒保健管理系
    關鍵字: 體適能
    測驗
    預測模式
    physical fitness
    test
    predictive model
    日期: 2005
    上傳時間: 2008-05-29 14:34:37 (UTC+8)
    出版者: 台南縣:嘉南藥理科技大學休閒保健管理系
    摘要: 本研究之主要目的在於探討健康體適能測驗項目間之預測關係進而建立其間之預測模式,以供大專體育老師協助無法完成測驗之學生,由建立之常模中預測出缺測項目之相對值,以進行整體體適能之評估。本研究以大學男生1685人、女生1510人分別實施正規之體適能測驗,項目包括有男生1600公尺跑女生800公尺跑、坐姿體前彎、一分鐘仰臥起坐、立定跳遠、以及身體素質指數(BMI)等五個項目。將所得的男女常模體適能測驗資料進行各項目間之皮爾遜積差相關後,選取有顯著相關之項目進行單純及多元回歸統計處理,以建構各個項目間之預測模式,做為各測驗項目間之測驗資料預測。研究資料經由SPSS電腦視窗版統計軟體10.0版處理後(α=.05),得到以下之結果:
    1. 總體適能分數不分男女幾乎都和各個檢測項目有顯著之相關。
    2. 身高和體重不分男女也有顯著之相關。
    3. 男生1600公尺跑和總體適能分數、體重、仰臥起坐、以及BMI之間有顯著之相關。女生800公尺跑則和總體適能、身高、體重、以及BMI之間有顯著之相關。
    4. 坐姿體前彎不分男女儘和總體適能分數之間有顯著之相關。
    5. 男生仰臥起坐和總體適能分數、1600公尺跑、以及立定跳遠之間有顯著之相關。女生仰臥起坐則和總體適能分數、及立定跳遠之間有顯著之相關。
    6. BMI不分男女都和總體適能分數、體重、1600公尺或800公尺跑之間有顯著之相關。
    基於以上之顯著相關基礎,進而建構成各體適能檢測項目間預測模式,以供大專體育教師測得缺測或漏測學生之體適能測驗資料,做為整體體適能評估之用,具有實際之應用與參考價值。
    The purpose of this study was to investigate the relationship among the tests of health-related physical fitness, and establish the predictive model for predicting the estimate test value among those items of tests. The subjects were included 1685 male students and 1510 female students from university. After receiving the tests of 1600m run for male and 800m run for female, sitting flexibility, one minute of sit-up, standing jump, and BMI, the data was utilized the Pearson Productive Correlation statistic treatment to figure out the relationship among those test items. Finally, the simple and multiple linear regression were used to establish those predictive models for estimating the missing data. The SPSS V.10 package for Windows was used for those data processing(α=.05), and the findings were found as followings:
    1. There was significant correlation between the total fitness score and each test item.
    2. There was significant correlation between height and weight for both male and female subjects.
    3. In male’s 1600m run, there were significant correlation with those tests of total fitness score, weight, sit-up, and BMI; in female’s 800m run, there were significant correlation with those tests of total fitness score, height, weight, sit-up, and BMI.
    4. There was significant correlation between sitting flexibility and total fitness score for both male and female subjects.
    5. There were significant correlation between male’s sit-up and those tests of total fitness score, 1600m run, standing jump, and there were significant correlation between female’s sit-up and those tests of total fitness score, standing jump.
    6. There was significant correlation between BMI and those tests of total fitness score, weight, 1600m or 800m run for both male and female subjects.
    According the correlation evidence listed above, the simple or multiple regression of predictive models were established for predicting the missing test data. Because of the large sample size, these predictive models could provide the practical application for those teachers teaching in the collage or university.
    Appears in Collections:[休閒保健管理系(所)] 校內計畫

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