In this paper, we propose a methodology for the analysis of questionnaire data along with its application on discovering insights from investor data motivated by a day trading competition. The questionnaire includes categorical questions, which are reduced to binary questions, 'yes' or 'no'. The methodology reduces dimensionality by grouping questions and participants with similar responses using clustering analysis. Rule discovery was performed by using a conversion rate metric. Innovative visual representations were proposed to validate the cluster analysis and the relation discovery between questions. When crossing with financial data, additional insights were revealed related to the recognized clusters.

翻译：本文提出了一套问卷调查数据分析方法论，并应用于从日内交易竞赛投资者数据中挖掘洞见。问卷包含分类问题，将其简化为二元问题（“是”或“否”）。该方法通过聚类分析，将具有相似回答的问题与参与者进行分组，从而降低数据维度。规则发现采用转化率指标完成。我们提出了创新的可视化表示方法，以验证聚类分析及问题间的关系发现。当与财务数据进行交叉分析时，与识别出的聚类相关的额外洞见得以揭示。