Data Analytics in Psychological Research

Psychological data are very complex to analyze and interpret because of its hidden structure. It is easily affected by random errors of individual differences, differences in situations and by the interaction of individual and environment. Another significance of psychological data is multi-dimensionality. One construct is assessed through multiple sub-constructs. Again, each sub-construct is assessed through multiple consistent attributes. For prediction, psychology follows system approach and big data. Traditional statistical tools sometimes fail to capture the gamut of psychological functions implied in the data. In this connection, data mining from big data warehouse is important. Padma Vibhushan, Professor C.R. Rao, Professor of the University of Buffalo defined big data as massive amounts of very high dimension and unstructured data which are continuously produced and stored with much cheaper cost than they are used to be. The massive samples in big data are typically aggregated from multiple sources at different time points using different technologies. Some of the static big psychological data are psychiatric case history records, answer sheets of Board level examination, selection test, data of disability, health insurance data, crime research data, industrial data. Social networking sites like Facebook, twitter, you tube are dynamic data warehouse. 

Topics

PSYCHOLOGICAL DATA SCIENCE


DATA RESERVOIR

INTRODUCTION TO DATA MINING

DATA DIMENSION REDUCTION ANALYSIS

SENTIMENT ANALYSIS OF SOCIAL MEDIA DATA