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# Fractional factorial design homework

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From: Lorenzo D.
Last week we began an experimental design trying to get at how to drive the golf ball the farthest off the tee by characterizing the process and defining the problem. We will construct a full factorial design, fractionate that design to half the number runs for each golfer, and then discuss the benefits of running our experiment as a factorial design. Many industrial factorial designs study 2 to 5 factors in 4 to 16 runs 2 runs, the half fraction, is the best choice for studying 5 factors because 4 to 16 runs is not unreasonable in most situations. The data collection plan for a full factorial consists of all combinations of the high and low setting for each of the factors. There are a number of good reasons for choosing this data collection plan over other possible designs. Here are my top five.

## Fractional factorial design - Wikipedia

Video 1 provides the introduction to the fractional factorial design of experiments. Video 1. What is Fractional Factorial Design of Experiments. For example, a 2 7 design of an experiment with seven variables of two levels for each factor will require unique experiments to complete one full replication of the design. Running experiments will be unnecessary and wasteful.

### Fractional Factorial Designs

Process Improvement 5. Choosing an experimental design 5. How do you select an experimental design?
This kind of design offers full flexibility as to the number of discrete levels for each factor in the design. Its usage is simple:. This function is a convenience wrapper to fullfact that forces all the factors to have two levels each, you simple tell it how many factors to create a design for:.

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