This course will enable the participant to plan the most cost-effective experiment or test which will result with a successful conclusion of the experiment or test objectives. It will show how properly designed tests are easily analyzed and prepared for presentation in a report or paper. Many companies are reporting significant savings and increased productivity from their engineering, process control and R&D professionals. These companies apply statistical methods and statistically-designed experiments to their critical manufacturing processes, product designs, and laboratory experiments. Multifactor experimentation, often called Design of Experiments (DOE), will be shown to increase efficiencies, improve product quality, and decrease costs. This first course in experimental design will start you into statistical planning before you actually start taking data and will guide you to perform hands-on analysis of your results immediately after completing the last experimental run. During the course, you will learn how to design practical full factorial and fractional factorial experiments. You will learn how to systematically manipulate many variables simultaneously to discover the few major factors affecting performance and to develop a mathematical model of the actual instruments. The course is taught with each participant assigned to a group that performs statistical analysis using a demo version of modern statistical software. At the end of this course, participants will be able to design experiments and analyze them on their own desktop computers. Because emphasis of the course is on practical implementation of DOE, each participant is highly encouraged to bring a laptop computer.