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Design of Experiments (DoE)

1) Type of Design

2) Factors

No. of Factors:
No. of Replicates:
No. of Blocks:
Factor Low High

3) Plan


Fractional Factorial Design Calculator

Here you can easily generat a Fractional Factorial Design online. Simply select the number of factors and the number of Runs. The Fractional Factorial Design Generator will then create your test plan. Further you can add the names of the factors.

Fractional Factorial Design Calculator

In a fractional factorial design, interactions can be confounded with other interactions or with main effects of factors. The extent to which the number of runs can be reduced at the expense of resolution is shown in this table.

Resolution Table Fractional Factorial Design

If you don't want to reduce the resolution, you can also use the Full Factorials Design calculator.

Fractional Factorial Design Generator

A Fractional Factorial Design is a type of experimental design used in the field of statistics and research. It is a subset of the full factorial design and is particularly useful when it's impractical or too expensive to conduct a full factorial experiment. Here are some key points about fractional factorial designs:

Key Points

  • Reduced Number of Experiments: Fractional factorial designs reduce the number of experiments by studying only a fraction of the possible combinations of factors and levels.
  • Efficiency in Screening: This approach is efficient for screening experiments to identify the most significant factors out of many, without running all possible experiments.
  • Resolution Levels: Characterized by their "resolution," which indicates the degree to which the design can estimate main effects and interactions without confounding. Higher resolution designs can separate more complex interactions but require more runs.
  • Trade-off Between Detail and Resources: These designs represent a trade-off between the completeness of the data and the resources required to collect it. They are chosen when the cost of a full factorial design is too high.
  • Statistical Analysis: Analysis often involves techniques like Analysis of Variance (ANOVA) and regression analysis to draw conclusions from the reduced dataset.
  • Applications: Widely used in industrial experiments, product design, process optimization, and quality improvement initiatives where there are many factors but limited resources.

Fractional factorial designs are a compromise that allows for a reasonable understanding of the system under study without the prohibitive costs of a full factorial design. They are useful in early experimentation stages to identify factors worth investigating more deeply.

Cite DATAtab: DATAtab Team (2024). DATAtab: Online Statistics Calculator. DATAtab e.U. Graz, Austria. URL

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