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Statistical Design and Analysis of Experiments

Before there was big data, little data was important. When data is precious, how should it be treated? How do you design tests to ensure that you learn the most for the cost?

This short course serves as an introduction to a statistical approach to the design and analysis of experiments in science, engineering, and data-driven decision making. The course will examine how to systematically design experiments and analyze the data they yield. The basis for comparing results and assigning significance to the variation in the responses that are measured is developed. Various experimental designs are discussed and their respective differences, advantages, and disadvantages are noted. In particular, factorial and fractional factorial designs are discussed in greater detail. These are designs in which two or more factors are varied simultaneously, in order to efficiently span the combinations of factors that affect the responses.

This course will be elementary in terms of mathematics. The course includes a review of the introductory probability and statistics background necessary for conducting and analyzing experiments. With this background, we first discuss the logic of hypothesis testing and, in particular, the statistical techniques generally referred to as Analysis of Variance. An overview of software packages is provided, including Microsoft Excel, JMP, and other more specialized packages.

Throughout the course we emphasize applications, using real examples ranging from manufacturing to digital marketing. All participants receive a copy of lecture notes and examples.

No dates are currently scheduled.

About the instructors

To be determined.

What to expect

The registration fee includes instruction, all necessary materials, parking on the VCU campus, a snack break and meal each session, and a Certificate of Completion. There is an optional fee of $30 to receive the 1.20 CEUs.

Ask about our VCU Alumni discount!

Who should attend

This course is perfect for entry-level scientists, engineers, and business managers of all types, and are appropriate as on-boarding for new employees to better understand the quantitative approach to understanding experimental systems and complex data sets. No previous training in probability and statistics is required, but a basic understanding of high school mathematics is anticipated.

Cancellation and Refund Policies

You may cancel your registration up until 7 days prior to the course start date, and receive a full refund minus any credit card processing fees. Cancellations must be received via email at ocpe@vcu.edu. In the unlikely event that this program is cancelled or postponed due to insufficient enrollments or unforeseen circumstances, the university will fully refund registration fees, but cannot be held responsible for any other expenses, including change or cancellation charges to include but not limited to airlines, hotels, travel agencies, or other organizations.