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Measurement Scales
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Measurement Scales
FOUR TYPES OF MEASUREMENT SCALES ARE: nominal, ordinal, interval, and ratio. It's important to know which type of scale is represented in the research data because different scales require different methods of statistical analysis. All variables are represented in at least one of the above measurement scale. That is, the variables represented nominal scale are named nominal variables, the variables represented ordinal scale are called ordinal variables and so forth. This article explains and compares the four kind measurement variables.
The following table is an overview of the comparision of 4 kinds of variables. It provides you a direction of reading this article.Properties Variables
Nominal Ordinal Interval Ration
Classify objects
Rank objects
Equal interval
True zero point-
Nominal Variables
Nominal variables, also called categorical variables, represent the lowest level of measurement. They simply classify persons or objects into two or more categories where members of a category have at least one common characteristic. Nominal variables include gender (female, male); employment status (full-time, part-time, unemployed); marital status (married, divorced, single); and type of school (public, private, charter). For identification purposes, nominal variables are often represented by numbers. For example, the category "male" may be represented by number 1 and "female" by the number 2. It is critically important to understand that such numbering of nominal variables does not indicate that one category is higher or better than another. The numbers are only labels for the groups.
Tall Short
Frankenstein is Tall; Igor is Short-
Ordinal Variables
Ordinal variables, like nominal variables, classify persons or objects but also rank them in terms of the degree to which they possess a characteristic of interest.In other words, ordinal variables put persons or objects in order from highest to lowest or from most to least.
However, ordinal variables do not indicate how much higher or how much better one person performed compared to another. In other words, intervals between ranks are not equal; the difference between rank 1 and rank 2 is not necessarily the same as the difference between rank 2 and rank 3. For example, consider the ranking of these four heights:RANK HEIGHT INTERVAL
1 6 ft, 5 in.
2 6 ft, 0 in. 5 inches
3 5 ft, 11 in. 1 inch
4 5 ft, 4 in. 7 inches-
Interval Variables (Nominal + Ordinal) + Equal interval
Interval variables have all the characteristics of nominal and ordinal variables, but also have equal intervals.Most of the tests used in educational research, such as achievement, aptitude, motivation, and attitude tests are treated as interval variables.
Frankenstein is 7 feet tall; Igor is 5 feet tall
Because of equal intervals, for example, the difference between a score of 30 and a score of 40 is essentially the same as the difference between a score of 50 and a score of 60. Interval scales, however, do not have a true zero point. A score of 0 does not indicate the total absence of knowledge but only indicates the lowest level of performance possible on a particular test and a score of 100 the highest level. Thus, we can say that a test score of 90 is 45 points higher than a score of 45, but we cannot say that a person scoring 90 knows twice as much as a person scoring 45.-
Ration Variables
Ration VariablesRation variables represent the highest, most precise, level of measurement. A ration variable has all the properties of the types already discussed. In addition, it has a true zero point. Height, weight, time, distance and speed are examples of ration scales. Because of the true zero point, we can say that a person 6 ft, 4 in. is twice as tall as one 3 ft, 2 in. Similarly, 60 minutes is three times as long as 20 minutes and 40 pounds is four times as heavy as 10 pounds.-
Author
Yu-Chan Cheng, EdTech Graduate Student -
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- 标签:
- score
- variables
- nominal
- scales
- rank
- interval
- represented
- measurement
- ft
- ordinal
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