Читать книгу Statistical Analysis with Excel For Dummies - Joseph Schmuller - Страница 15

Data come in four kinds. When you work with a variable, the way you work with it depends on what kind of data it is.

The first variety is called nominal data. If a number is a piece of nominal data, it’s just a name. Its value doesn't signify anything. A good example is the number on an athlete’s jersey. It’s just a way of identifying the athlete. The number has nothing to do with the athlete’s level of skill.

Next come ordinal data. Ordinal data are all about order, and numbers begin to take on meaning over and above just being identifiers. A higher number indicates the presence of more of a particular attribute than a lower number. One example is the Mohs scale: Used since 1822, it’s a scale whose values are 1 through 10; mineralogists use this scale to rate the hardness of substances. Diamond, rated at 10, is the hardest. Talc, rated at 1, is the softest. A substance that has a given rating can scratch any substance that has a lower rating.

What’s missing from the Mohs scale (and from all ordinal data) is the idea of equal intervals and equal differences. The difference between a hardness of 10 and a hardness of 8 is not the same as the difference between a hardness of 6 and a hardness of 4.

Interval data provide equal differences. Fahrenheit temperatures provide an example of interval data. The difference between 60 degrees and 70 degrees is the same as the difference between 80 degrees and 90 degrees.

Here’s something that might surprise you about Fahrenheit temperatures: A temperature of 100 degrees isn’t twice as hot as a temperature of 50 degrees. For ratio statements (twice as much as, half as much as) to be valid, zero has to mean the complete absence of the attribute you're measuring. A temperature of 0 degrees F doesn’t mean the absence of heat — it’s just an arbitrary point on the Fahrenheit scale.

The last data type, ratio data, includes a meaningful zero point. For temperatures, the Kelvin scale gives ratio data. One hundred degrees Kelvin is twice as hot as 50 degrees Kelvin. This is because the Kelvin zero point is absolute zero, where all molecular motion (the basis of heat) stops. Another example is a ruler. Eight inches is twice as long as four inches. A length of zero means a complete absence of length.

Any of these data types can form the basis of an independent variable or a dependent variable. The analytical tools you use depend on the type of data you’re dealing with.