Electronic survey research results in a database of information. Retrievable data from survey responses can be individually validated and used to create models including polynomials, orthogonal series, splines, and other types of (possibly nonlinear) regressors, as well as a variety of methods for directly estimating probability densities, such as kernels and histograms. See below for a list of useful display chart types for displaying information analysis results.

Data Mining
Some data sets are extremely large and often times it is required to gather an incredibly large amount of data to find a particular answer or solution. Custom built data mining scripts, modules, and software can help mine your data to provide very specific results.

Microsoft Office Integration
Respondent data is traditionally imported into a database or Excel array whereas one can run real-time data scenarios, case studies, and goal seeks on your data sets. Depending on what deliverables your project requires, we can provide dynamically updating online WG Platforms, SQL databases, self calculating Web Query documents, Online Pivot Charts, Online Pivot Tables, and Publishable PDFs.

Links of Interest

• Department of Sociology at the University of Maryland
• Washington Post Audience Research
• Excellent Use of SSR: Usage and Purchasing Habits of Affluent Online Adults

Information Analysis Results

• Predictive Trend Analysis
• Bar charts (e.g. top information needs by categories)
• Column bars (e.g. 3D information landscape)
• Pie charts (e.g. top five information sources by percentage usage)
• Scatter plot (e.g. to identify and group categories of information by frequency)
• Area plot (e.g. 2D information landscape)
• Cone and pyramid plots
• Doughnut plot (e.g. information need by percentage by department or division)
• Bubble plot (scatter plot that supports a third variable; e.g. information need by department, category and value of information)