A z-score is a way of placing the measurement of a particular person (的繁體中文翻譯

A z-score is a way of placing the m

A z-score is a way of placing the measurement of a particular person (for example, a person’s body mass index [BMI], a marker of body weight) in the context of what that measurement is for other people in the population. It relies on knowing what the average (or “mean”) is for the whole population and the variability (how frequently and how much people are different from average, measured in terms of standard deviation). Technically, a z-score is the number of standard deviations from the mean a particular value is. A z-score=0 for a given individual indicates the value for that individual is equal to the mean of the population. A z=2 means that the value is 2 standard deviations above the mean of the population, meaning much “above average”. There are corresponding percentiles that are meaningful: a z=0 is equivalent to the 50th percentile, again indicating that 50 percent of the population has lower MetS severity than the individual. A z=2 is equivalent to the 97.7th percentile, indicating that 97.7% of the population has a lower MetS severity than the individual. Z-scores can be negative as well; z=-2 is the 2.28th percentile, meaning only roughly 2% of the population has a lower MetS severity.
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結果 (繁體中文) 1: [復制]
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A z-score is a way of placing the measurement of a particular person (for example, a person’s body mass index [BMI], a marker of body weight) in the context of what that measurement is for other people in the population. It relies on knowing what the average (or “mean”) is for the whole population and the variability (how frequently and how much people are different from average, measured in terms of standard deviation). Technically, a z-score is the number of standard deviations from the mean a particular value is. A z-score=0 for a given individual indicates the value for that individual is equal to the mean of the population. A z=2 means that the value is 2 standard deviations above the mean of the population, meaning much “above average”. There are corresponding percentiles that are meaningful: a z=0 is equivalent to the 50th percentile, again indicating that 50 percent of the population has lower MetS severity than the individual. A z=2 is equivalent to the 97.7th percentile, indicating that 97.7% of the population has a lower MetS severity than the individual. Z-scores can be negative as well; z=-2 is the 2.28th percentile, meaning only roughly 2% of the population has a lower MetS severity.
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結果 (繁體中文) 2:[復制]
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z-Score 是將特定人員的測量(例如,一個人的體重指數 [BMI],體重的標記)放在該測量對人口中其他人的指標的上下文中的一種方式。它依賴于瞭解整個人口的平均值(或"平均值")和可變性(以標準差衡量,人口與平均值的差異頻率和差異程度)。從技術上講,z 得分是特定值的平均值的標準差數。給定個人的 z-Score=0 表示該個體的值等於總體的平均值。z=2 表示該值比總體平均值高出 2 個標準差,這意味著"高於平均值"。有有意義的相應百分位數:z=0 等效于第 50 個百分位數,再次表明 50% 的人口具有比個人更低的 MetS 嚴重性。z=2 等效于 97.7 百分位數,表示 97.7% 的人口具有比個人更低的 MetS 嚴重性。Z 分數也可以為負數;z_-2 是第 2.28 個百分位數,這意味著只有大約 2% 的人口具有較低的 MetS 嚴重性。
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結果 (繁體中文) 3:[復制]
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z分數是一種將對某個人的量測(例如,一個人的體重指數[BMI],一個體重的標誌)放在對人群中其他人的測量範圍內的方法。它依賴於知道整個人口的平均值(或“平均值”)是什麼以及變異性(根據標準差衡量,人們與平均值的差异有多頻繁、有多大)。從科技上講,z分數是指某一特定值的平均值的標準差的數量。給定個體的z得分=0表示該個體的值等於總體的平均值。A z=2表示該值高於總體平均值的2個標準差,這意味著“高於平均值”。有相應的百分位數是有意義的:z=0相當於第50個百分位數,再次表明50%的人口比個人有更低的MetS嚴重性。A z=2相當於97.7個百分點,表明97.7%的人口有較低的MetS嚴重程度比個人。Z分數也可以是負的;Z=-2是2.28個百分點,這意味著只有大約2%的人口有較低的MetS嚴重程度。<br>
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