I am frequently asked the question what is "Statistical Consulting?" Statistical consulting is actually a very broad term as is the science of statistics. Statistics is defined as the science of making effective use of numerical data. A statistical consultant makes use of the science of statistics to solve a real world problem while also providing qualitative consultation and technical expertise.

The process of statistical consulting is varied depending on the research topic on hand. A client needs to determine the research topic to explore. Immediate issues to consider are the collection of data. Does a survey need to be created? How is the data going to be collected? If consumers are going to be surveyed, a properly constructed survey and determining randomization techniques are imperative. How many consumers must be surveyed to obtain the desired level of power? An example could be a consumer products company that is looking to increase sales of a product line of toothpaste. The company wants to create a marketing campaign to market to groups that are most likely to purchase the product. Once consumers are properly surveyed the data needs to be analyzed. A good consultant needs to be able to work with large datasets as data storage and management is an extremely important part of the process. After determining data methods, the consultant needs to be able to work with a statistical software package to manipulate the data, make inferences, and conclusions. When using a package it is important to use the package most appropriate for the organization as one package may be a better fit based on many factors. After making conclusions, the consultant needs to be able to present and implement the results to the company and into their technology process. Although this process is very quantitative, there is an art component as well which comes from being able to understand the goal of the client and successfully relate the science of the results. Cost is always an issue as well with a study and determining the power. It may not be cost effective to survey thousands of consumers and in situations like this the consultant needs to determine the best solution to maximize the accuracy of the study.

Another example is a utility company that needs to know how much natural gas they are going to need on a daily basis to heat homes in the winter time. If the company has too much supply it needs to be stored which is an added cost. Too little supply and it is possible to have a shortage. An optimal amount needs to be determined depending upon factors such as temperature, wind speed, and average household usage.

I've worked on many different types of projects in many different industries but specialize in building predictive models for decision making processes. A predictive model is a mathematical or statistical formula or process that takes a variety of inputs and allows an end user to make predictions about an event, product, or situation under certain assumptions. Predictive modeling allows a company to maximize or minimize a process and identify both opportunity and risk. Often, it is more important to identify risk than opportunity.