Basic Statistics & Design of Experiments (DOE)

Register June 15 - 17, 2020 (on-campus)

Register June 15 - 30, 2020 (blended online)

At-a-Glance

How can you determine if a new process performs better than the original? How can you be confident that a new drug or vaccine will be safe and effective?  How can you best determine which market(s) to target a new product?  Reliable answers to questions like these are found by collecting data from properly designed tests, trials, or experiments.  Too often organizations use informal methods (eg. opinions) or poorly designed experiments to make important decisions.  Experimental design is a way to carefully plan experiments in advance so that your results are both objective and valid. Effective experimental design and analysis are critical to improving products and processes, reducing waste, lowering costs, and improving productivity.

This how-to workshop focuses on understanding the fundamental elements of experimental design and how to apply experimental design to solve real problems.  A statistical software package, Minitab®, is used to help create designs, analyze data, and interpret results more efficiently and effectively. We will examine how to use proven statistical methods to properly design, collect, and analyze experimental data.

1) On-campus option

The on-campus workshop is offered over a 3-day period.  Each topic is reinforced through discussion, case studies, exercises, and simulations.  Exercises and simulations are conducted in our computer lab using Minitab statistical software.  Outside of class, participants are welcome to join online discussions with the instructor and other students.

2) “Blended online” option

The online instructor-led workshop covers the same material as the 3-day on-campus program but is available over a 2-week period through our online Learning Management System, providing flexibility to your schedule.  Learning materials include pre-recorded lectures, case studies, exercises, and simulations.  We keep you actively engaged through online discussions with the instructor and other students. (If you don’t have access to Minitab software, go to www.Minitab.com to download a free trial copy).

Topics

• One-factor-at-a-time experiments - what your competitors want you to use
• The importance of a strategy of experimentation
• Summarizing results in experiments - main effects and interactions
• Two-level designs for 3-5 factors - the 2k designs
• Variation when conditions are held constant -  a review
• The importance of randomizing and blocking in experiments
• Handling variation naturally in two-level designs
• The value of non-replicated experiments
• How to select the correct number of runs for an experiment
• The role of center points and how to use them correctly
• Fractional factorial (2k–p) designs - studying 5-15 factors, or more efficiently
• The use of fold-over designs to gain more information
• Case studies, simulations, and exercises
• Using Minitab® to, help create designs and interpret results

Who Should Attend

Professionals in engineering, R&D, manufacturing, quality, and marketing who plan, conduct, analyze, and interpret tests to evaluate the impact of key parameters on the performance of products and processes.  Learn how to select the most effective design to answer important questions that maximize results while minimizing time and effort.

Certification

A “certificate of completion” from RIT’s Center for Quality and Applied Statistics is issued upon completing the program including all assigned exercises.