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Measurements and Design

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1) I am having difficulty trying to explain in one paragraph how to differentiate between the levels of measurement by providing an example of data that can be transformed from one level of measurement to another and also another example of data that cannot be transformed. I also have to include in this paragraph an explanation for why some data can be transformed and some cannot.

2) Also, I have to try to compare in two paragraphs the concept of validity for design to the concept of validity for measurement.

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This solution describes how to differentiate between the levels of measurement that can be used to assess data and comparing validity for design and validity for measurement.

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1) There are four levels of measurement (nominal, ordinal, interval, and ratio). Briefly, nominal scales use numbers for identification only; the values are not on a number scale. An example of a nominal scale is hockey jersey numbers, or identifying the genders using numbers (male = 1, female = 2). Ordinal scales rank values, so scores are in order but only by ranks. An example of an ordinal scale would be having people report their preference for four different types of soda pop, from most preferred to least preferred. Interval scales put values on a true number scale, but the scale does not have a true zero point, while ratio scales have scores on a number scale that has a true zero (for example, height or age). For the purposes of many statistics, we often collapse interval and ratio scales into one category, since it usually doesn't matter for analyses whether or not the scale has a true zero.

You can often measure age on an ordinal or ratio scale. For example, you could have people report their ...

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