1.5: 测量的序数水平

Ordinal Level of Measurement
JoVE Core
Statistics
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JoVE Core Statistics
Ordinal Level of Measurement

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00:55 min
April 30, 2023

Overview

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.

Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks in the United States. These parks can be ranked from one to five based on size and biodiversity, but the differences among those ranks cannot be measured. Another example of  ordinal scale data is a cruise survey where the responses to questions about the cruise are “excellent,” “good,” “satisfactory,” and “unsatisfactory.” These responses can be arranged from the most desired response to the least desired. However, it is not possible to measure the differences between any two pieces of data. Ordinal scale data cannot be used in calculations like the nominal scale data.

This text is adapted from Openstax, Introductory Statistics, Section 1.3 Frequency, Frequency Tables, and Levels of Measurement

Transcript

名义、序数、区间和比率是测量的四个级别。

如果数据可以按特定顺序排列,则它属于 Ordinal 级别的测量。但是,数据值之间的差异没有意义或无法确定。

例如,如果最近发行的电影按 1 到 5 的等级进行分级,则会创建一个有序数据集。

在这里,五星评级的电影比一星的电影好,但是他们的评级差值(四星)没有关于电影演员、故事或视觉效果的有意义的信息。

二分值,例如 health 或 sickness,或 innocent 或 guidty 也是有序测量级别的示例。在这里,像比另一个人更无辜或更健康这样的问题是没有意义的。

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