Making Decisions from Data: All science and business depends upon making correct decisions in a timely manner on the minimum necessary data.

Signal or Noise: All data contain noise; some data contain signals. As a result, there is always some risk of drawing the wrong conclusion from experimental data.

Statistics provides tools to tell the difference between signal and noise and to control the risk of error.

Experimental Design provides a set of planning methods to minimize these risks and limit the amount of data needed (aka co$t).

One-Factor-At-A-Time Methods: The majority of academic training that scientists receive stress the need to be rigorous and methodical about one's experimental plan. However, this very same training often is incorrect in recommending that we hold all other experimental factors constant while we study the single topic of interest. It turns out that this is bad advice. Click here for a simple example of why this is so.

Mission

Haag Consulting provides consulting services, corporate training and technical support in the use of experimental design and  statistical methods for making accurate decisions based upon the minimum necessary experimental data.