Cross tabulation is a method used when creating graphs which display how different items inter-relate. This allows those creating and reviewing the graphs to see where two or more pieces of data directly relate to or affect one another. Cross tabulation is typically used in surveys, market research and sometimes even financial reports when it is clear that the multiple pieces of information affect each others’ outcome.
The use of cross tabulation is also sometimes referred to as a chi-square. The way these tables are set up shows the results of multiple variables when compared against each other. For example, a person may be creating a table of how many men and women drive green cars versus blue cars. To gather the data, this person would have to interview several people and write the information down. If he interviewed 40 people, the table he created from this data may look something like this:
| Gender | Green Car | Blue Car |
| Male | 9 | 13 |
| Female | 12 | 6 |
Cross tabulation has benefits even in everyday life. A person may use it to track her family’s monthly spending over a period of time, and even school children are often taught to compile simple data this way. A visual representation of large amounts of variable data is typically easier for people to understand than pages and pages of written data.
In industry, data like this is very important when attempting to forecast markets trends, review financial variables over a long period of time and even track the health records of an entire country. It is very common for these tables to include many variables, and several different tables may even be grouped together which compare and contrast dozens of elements. Cross tabulation has use in many areas like marketing, product management and sometimes even in staff research.
The process of cross tabulation tends to give a more complete picture of past and current trends as well as possible future outcomes. It helps those analyzing the data gain an understanding of what factors affect their given elements, form hypothesis of what may happen if new information or an element is added, and see what information is not in their forecasts that should be.
The cross tabulation method has been around for many years, but in the past, people were forced to manually gather, organize and compile all the data into hand-made tables and reports. In modern times, this is generally done with computer programs which can organize the data, add up complex mathematical problems and create full tables almost automatically. Then it is simply up to the user to check the information for discrepancies or errors and present the information to the appropriate people.