Data at this level can be ordered, but no differences between the data can be taken that are meaningful.
An interval variable is similar to an ordinal variable, except that the intervals between the values of the interval variable are equally spaced. For example, suppose you have a variable such as annual income that is measured in dollars, and we have three people who make $10,000, $15,000 and $20,000. A categorical variable (sometimes called a nominal variable) is one that has two or more categories, but there is no intrinsic ordering to the categories. For example, gender is a categorical variable having two categories (male and female) and Level of measurement or scale of measure is a classification that describes the nature of information within the numbers assigned to variables. The best known classification is that developed by the psychologist Stanley Smith Stevens, who proposed four levels, or scales, of measurement: nominal, ordinal, interval, and ratio. Level of measurement refers to the way that a variable is measured. There are four main levels of measurement that variables can have: nominal, ordinal, interval, and ratio. Being familiar with the level of measurement of the variables in your data set is crucial because they will help determine what statistical procedure you use. Ratio Level Of Measurement. Variables that are measured at the ratio level are similar to interval variables, however they have an absolute zero that is meaningful (i.e. no numbers exist below zero). That is, you can construct a meaningful ratio, or fraction, with a ratio variable. The crux of the matter is the relationship between the variable's level of measurement and the statistics that can be meaningfully computed with that variable. For example, consider a hypothetical study in which 5 children are asked to choose their favorite color from blue, red, yellow, green, and purple. On the other hand, ordinal scales fail to capture important information that will be present in the other scales we examine. In particular, the difference between two levels of an ordinal scale cannot be assumed to be the same as the difference between two other levels. For example, an interval level of measurement could be the measurement of anxiety in a student between the score of 10 and 11, if this interval is the same as that of a student who is in between the score of 40 and 41. The first level of measurement is nominal measurement. In this level of measurement, the numbers are used to classify the data. Also, in this level of measurement, words and letters can be used. Suppose there are data about people belonging to two different genders. 1 A interval variable is a measurement where the difference between two values is meaningful. 2  The difference between a temperature of 100 degrees and 90 degrees is the same difference as between 90 degrees and 80 degrees. 1 A ratio variable, has all the properties of an interval variable, and also has a clear definition of 0.0. 2  When the variable equals 0.0, there is none of that variable. 3  Variables like height, weight, enzyme activity are ratio variables. 4  Temperature, expressed in F or C, is not a ratio variable. Ordinal Level of Measurement. The next level is called the ordinal level of measurement. Data at this level can be ordered, but no differences between the data can be taken that are meaningful. Here you should think of things like a list of the top ten cities to live. Ordinal. An ordinal variable is similar to a categorical variable. The difference between the two is that there is a clear ordering of the variables. For example, suppose you have a variable, economic status, with three categories (low, medium and high). A categorical variable (sometimes called a nominal variable) is one that has two or more categories, but there is no intrinsic ordering to the categories. For example, gender is a categorical variable having two categories (male and female) and That is why it is best to use the highest level of measurement possible when collecting information. In this video nominal, ordinal, interval and ratio levels of data will be described in order from the lowest level to the highest level of measurement. By the end of this video you should be able to identify the level of measurement being used in a study. 
http://www.ats.ucla.edu/stat/mult_pkg/whatstat/nominal_ordinal_interval.htm https://en.wikipedia.org/wiki/Level_of_measurement http://sociology.about.com/od/Statistics/a/Levels-of-measurement.htm http://onlinestatbook.com/2/introduction/levels_of_measurement.html http://www.statisticssolutions.com/data-levels-of-measurement/ http://graphpad.com/support/faqid/1089/ http://statistics.about.com/od/HelpandTutorials/a/Levels-Of-Measurement.htm http://www.ats.ucla.edu/stat/mult_pkg/whatstat/nominal_ordinal_interval.htm http://www.youtube.com/watch?v=LPHYPXBK_ks
ordinal level of measurement definition statistics