The relationship is determined when the two variables form a matrix. That is, if variable A has two possible responses and variable B has three possible responses, a 2 x 3 matrix is formed that results in six cells that represent all of the possible combinations of responses between the two variables. The basis for the analysis is to determine the expected value for each of the cells in the matrix. The expected value represents the proportionate number of respondents that would be expected to fall in that cell if the two variables being studied were perfectly independent of one another. Also recorded in each cell is the actual number of respondents who answered in that particular combination of responses between the two variables.
Significance is measured in terms of the p-value.
A dependent relationship between the two variables is most often suggested when the corresponding p-value is less than the .05 value. An even stronger dependent relationship between the two variables is suggested when the p-value is less than the .01 value. However, if a substantial number of differences were found to exist, then the differences might be used as a basis to segment the large Non-Client market. Each of the 2,687 small businesses that were shown as current SBDC Clients were sent a questionnaire that corresponded to their business type. The overall response rate for this group was 13.2 percent.