I think this is a litle better than the schweser explaination…hope it helps Two days. Nominal Scale: A nominal scale is really a list of categories to which objects can be classified. For example, people who receive a mail order offer might be classified as “no response,” “purchase and pay,” “purchase but return the product,” and “purchase and neither pay nor return.” The data so classified are termed categorical data. Ordinal Scale: An ordinal scale is a measurement scale that assigns values to objects based on their ranking with respect to one another. For example, a doctor might use a scale of 0-10 to indicate degree of improvement in some condition, from 0 (no improvement) to 10 (disappearance of the condition). While you know that a 4 is better than a 2, there is no implication that a 4 is twice as good as a 2. Nor is the improvement from 2 to 4 necessarily the same “amount” of improvement as the improvement from 6 to 8. All we know is that there are 11 categories, with 1 being better than 0, 2 being better than 1, etc. Interval Scale: An interval scale is a measurement scale in which a certain distance along the scale means the same thing no matter where on the scale you are, but where “0” on the scale does not represent the absence of the thing being measured. Fahrenheit and Celsius temperature scales are examples. Ratio Scale: A ratio scale is a measurement scale in which a certain distance along the scale means the same thing no matter where on the scale you are, and where “0” on the scale represents the absence of the thing being measured. Thus a “4” on such a scale implies twice as much of the thing being measured as a “2.” http://www.statistics.com/resources/glossary/r/ratioscale.php