ABSTRACT
The research data can be analyzed using various statistical measures and inferring conclusions from these measures. Figure 6.1 presents the steps involved in analyzing and interpreting the research data. The research data should be reduced in a suitable form before it can be used for further analysis. The statistical techniques can be used to preprocess the attributes (software metrics) so that they can be analyzed and meaningful conclusions can be drawn out of them. After preprocessing of the data, the attributes need to be reduced so that dimensionality can be reduced and better results can be obtained. Then, the model is predicted and validated using statistical and/or machine learning techniques. The results obtained are analyzed and interpreted from each and every aspect. Finally, hypotheses are tested and decision about the accuracy of model is made.
