STATISTICAL CONSULTING

One of our core specialties is developing sound statistical methodologies to analyze business problems, and then carrying out the requisite data analyses to solve those problems.

We embrace firms that come to us for solutions to specific issues. However, we also embrace firms that come to us with vaguely-posed business problems. In such circumstances we specify the problem statistically ourselves, and find robust and practical solutions that do not succumb to data-snooping pitfalls. Our first step is always to fully understand the problem and the data available to us in solving that problem. Given the type and amount of data available, we then determine the optimal statistical methodology to solve the problem. Alternatively, in the case of the firm having no relevant data, our first step would be to create the optimal methodology to collect the needed data. In many business problems, the data available can be incomplete, disorganized, or unwieldy. In these cases, we often need to find a clever way to extract useful info out of the available data, and/or to supplement that data with additional data.

Our comfort with virtually all higher-level quantitative methodologies and our expertise in applying these tools in a corporate setting enables us to assist with virtually any quantitavie business problem. Here is a  very restricted sample of some of the analytical tools we use in solving quantitative problems:

• Survey Development and Reliability/Validity testing of existing surveys:
• Various forms of Regression Analysis, including Non-Linear Regression and Ridge Regression
• Survival Analysis including Kaplan-Meier Analysis
• Time Series Analysis, including Vector Autoregression (VAR), Vector Error-correction Models (VECM)
• Statistical Power Analysis for Sample Size determination
• Multivariate Analysis (with multiple outcome variables), such as MANOVA and MANCOVA.
• Optimization methods such as Linear and Nonlinear Programming and Simulated Annealing
• Markov Models, Monte Carlo Simulation and similar methods
• Stochastic modeling and simulation
• Nonparametric Models

The above list is intended to give some insight but is not exhaustive.