Pie chart or bar graph is usually used for categorical variables. Pie chart shows relative values, but it cannot be used, if the observation belongs to multiple categories. [br][br]

Bar graph enables cluster comparisons in a meaningful way. If there is a natural ordering between categories, it can be displayed on horizontal axis of the graph.

A discrete variable can either have  finite number of values  ({1.1, 1.3, 1.5}) or countably infinite number of single unequal values (natural numbers). A continuous number can be any real number (uncountably  infinite). [br][br]Frequency table describes the number of unequal values. For categorical and discrete variables it means counting the number of observations for each unequal value. If a graph is used, it is usually a [i]histogram[/i] . Sometimes , there are used [i]percentual frequencies [/i]and [i]relative frequencies[/i]. You should look at medium, spread, shape, skewness, and possible outliers of the histogram, when interpreting it. Shape should follow the Normal distribution. [br][br]

Countably infinite variables and continuous values should be classified before frequencies. Usually, classifying loses specific information but desbribes general features more clearly. Classifying and frequencies can be done with stem-and-leaf, in which case not so much information is lost. [br]