# What is a split plot factorial design?

## What is a split plot factorial design?

The split-plot design is an experimental design that is used when a factorial treatment structure has two levels of experimental units. The whole plot is split into subplots, and the second level of randomization is used to assign the subplot experimental units to levels of treatment factor B.

## How do you do fractional factorial design?

The fraction of trials required is calculated using this formula: 1/(lp). For example, an experiment with two levels per treatment factor and two confounded interactions would require 1/(22) or 1/4 of the trials required for a full factorial design.

**What is the difference between full factorial design and fractional factorial design?**

As the number of factors in a 2-level factorial design increases, the number of runs necessary to do a full factorial design increases quickly. A half-fraction, fractional factorial design would require only half of those runs.

**What is the major use of fractional factorial designs?**

The basic purpose of a fractional factorial design is to economically investigate cause-and-effect relationships of significance in a given experimental setting.

### What are the advantages and disadvantages of split plot design?

Advantages and Disadvantages Compared to completely randomized designs, split-plot designs have the following advantages: Cheaper to run. In the above example, implementing a new irrigation method for each subplot would be extremely expensive. More efficient statistically, with increased precision.

### What makes a split plot design different than a factorial design with blocking?

The split-plot design in this example has only one whole-plot factor and one subplot factor. The key difference between split-plot designs and randomized block designs is that, in randomized block designs, the factor level combinations are randomly assigned to the experimental units in the blocks.

**What is two-level fractional factorial design?**

Extending the notation of earlier chapters, we designate as 2 k − p fractional-factorial designs the two-level designs where k indicates the number of factors to be studied and 2 k − p gives the number of treatment combinations to be used. Thus, a 23–1 design is one with three factors and four treatment combinations .

**What is 2 level factorial design?**

Full two-level factorial designs are carried out to determine whether certain. factors or interactions between two or more factors have an effect on the response. and to estimate the magnitude of that effect.

## What are the disadvantages of split plot design?

This type of design does have many disadvantages, including:

- Implementing the design can be difficult, and requires advanced knowledge of a specific discipline (e.g. agriculture, factory production, or epidemiology).
- Software packages that assist with the design are hard to find, although SAS and JMP have options.

## When would you use strip plot design?

Strip-plot designs (also called split-blocks) were originally used in wheat experiments (hence the word “plot” in the name). Today, they are also widely used in business and industry. Let’s say you had two factors A and B, each of which require large plot areas. Both factors have multiple levels a and b.

**Why we use split split plot design?**

The split-split plot arrangement is especially suited for three or more factor experiments where different levels of precision are required for the factors evaluated. This arrangement is characterized by: 1.