An intelligent questionnaire analysis expert system
In the questionnaire analysis, how to find a statistically significant difference between two or more groups in a continuous measure is one of the major problems in researches. However, it is difficult for researchers to solve the issue of finding possible statistically significant difference. There are two causes of this issue. The one is that the process of finding the statistically significant differences is highly dependent on researchers intuition and experience, and the other is that the original questionnaire data may not be good enough to find the statistically significant differences. In this paper, we build a data warehouse and a forward-chaining rule-base expert system with three kinds of indicators, Increase, StepDown, and Dice, for drilling down the data warehouse to assist researchers in exploring the data to select appropriate statistics methods to find possible significant differences. The prototype of this expert system has been implemented, and the results of experiment about satisfaction survey showed finding the significant difference becomes easier, and users were interested in the idea of this system.
expert system statistically significant difference data warehousing on-line analytic processing (olap)