Capabilities Performance Management | Program Evaluation Simulation Modeling | Statistical Modeling | Survey Analysis Customer Profiling | Relocation & Economic Development Statistical Modeling EconSys analysts are trained in many types of research designs. In analyzing data, our staff utilize the most advanced statistical and mathematical applications, including time-series forecasting, generalized least square econometrics, logit and probit categorical dependent variable analysis, survival modeling, causal path modeling, and analytic hierarchy process. In addition, we have developed many in-house computer programming routines for tackling various specialized research topics. Data mining programming and tools search data warehouses for finding solutions that are then implemented in real-world situations. Listed below are some of the data-mining methodologies employed by our firm: •      Causal Path Modeling (CPM) is a comprehensive approach that can be         used to analyze multiple linkages between variables, even those         variables that are influential yet not directly observable. CPM is an         advanced statistical tool based on structural equation modeling         technique. •      Neural network (artificial intelligence) programming is used to sift         through data for patterns that will predict behavior and uncover         hidden, often non-linear, patterns. •      Cluster analysis is used to group similar people together based on         similar data characteristics. •      Discriminant analysis is a classification method that measures the         importance of factors determining membership within a defined         category. •      Decision Trees utilizing CHAID and CART algorithms separate out         data into sets of rules which are likely to have a different effect on a         target variable.