and dependent variables assessed, the various tests to be performed on the inputs are constructed and the possible errors are evaluated.
Analyse Data: After the experiment is carried out as designed, the data is collected for analysis at this stage. Possible results are formulated. This project is centered on providing automation aid to researchers at this stage where they want to analyse the data.
Interpret Results: The results obtained are then articulated to form solid conclusions. In this project, the results may be in form of a graphical visualisation supported by some statistical figures highlighting the population chosen for comparison for biases.
Verify Predicted Results: Based on the errors found in step 4, the results are verified again and the evidences are presented as conclusions. Any scope for uncertainties is resolved. This stage goes beyond the scope of the project; however, data is set up in a manner that would be effectively read into a statistical package for inferences.
Figure 4. DOE Process [8]
2.4.4 Advantages and Disadvantages of DOE A major advantage of experimental design is that it can help signify causality (causeand-effect relationship) if conducted thoughtfully. For example, “a psychologist may conduct an experiment on finding the degree to which children watching violent TV shows tend to aggress at their classmates in the playground.” [9]. A good experiment can help the experimenter to manipulate sufficiently. This may be controlling the exposure of children to violent television to 9