Frequency tables are the easiest of the bunch to build, in a visual sense and in terms of complexity. Pictured here is a table using the data above. With the assumption that your raw data won’t resemble a table already, assembly is still quite easy. Construct two columns and label them accordingly: the left column is your qualitative data, meaning that it represents a category rather than a numerical value, which is your quantitative data. Your quantitative data goes in the right column. Continuing with our example, you can see the categories aligned in separate rows on the left, and their frequency recorded in each respective row.

From here you can extrapolate data as needed: divide each quantitative value by the sum of frequencies and multiple by one hundred, and you have each category’s percentage frequency! Calculating percentages can be a lot easier than trying to move around six, seven, and eight-plus digit numbers. Again, our example is fairly simple on its own, but if we had been working with a greater number of categories or larger frequencies, then building a table like this and calculating percentage is a useful tool! To plug this all back into our example, however, we would determine the percentage frequency of each category using the above method, which gives us a result of: 46.67% Blue, 20% Green, and 33.33% Red. 

There is a plethora of ways the information we gathered and assessed can be useful! Perhaps you’re a teacher who wants to make sure they have enough crayons for everybody to use. If you only have one or two shades of blue, then this data may prompt you to get more blue crayons. Or maybe you want to help you students with a mural and need to know what colors the students will appreciate most. The possibilities truly are endless, and the benefits of analyzing your business this way are endless as well!