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Glossary

Design of Experiments

Glossary of Design of Experiments.

The design of experiments (DOE, DOX, or experimental design) is the design of any task that aims to describe and explain the variation of information under conditions that are hypothesized to reflect the variation. The term is generally associated with experiments in which the design introduces conditions that directly affect the variation, but may also refer to the design of quasi-experiments, in which natural conditions that influence the variation are selected for observation.

Topics Statistics Engineering

Terms listing

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2-Level Design 3-Level Design

A

Aliased Effects Aliases Aliasing ANOVA ARL Arrays Average Run Length Axial Distance

B

Balanced Design Balanced Incomplete Block Designs Balanced One-Way Design Balanced Randomized Block Design BIB Block Block Effect Blocked Design Blocking Variable Box-Behnken Design Brainstorming

C

Causality Centerpoint Central Composite Design Confidence Interval Confounded Effects Confounding Contour Plot Controllable Factors Cube Plot Curvature Curvature Check

D

D-Optimal Designs Daniel Plot Defining Relationship Degrees of Freedom Design Design Generators Design Matrix Design Point Design Resolution (III, IV, V, or V+)df Draper-Lin Small Composite Design

E

Effect Empirical Data Empirical Model Experimental Condition Experimental Design Experimental Factor Experimental Region Extreme Vertices Designs

F

F F-Ratio Face-Centered Design Factor Factor Effects Factor Level Factorial Design Fitted Model Foldover Design Fractional Factorial Design Full Factorial Design

G

Graeco-Latin Square Designs

H

Half-normal Plot

I

Inner/Outer Arrays Interaction Interaction Effect

L

Latin Square Designs Level

M

Main Effect Metric Variable Mixture Experiment Model Fitting Multi-Factor Categorical Designs Multilevel Factorial Design Multiple Regression

N

Noise Nonmetric Variable Normal Distribution Normal Plot Nuisance Variables

O

One-Factor-at-a-Time Experimentation One-way Design Orthogonal design

P

P-Value Pareto Chart Partial confounding Path of Steepest Ascent Path of Steepest Descent Plackett-Burman Design Pure Error

R

Randomization Randomized Block Design Replication Response Surface Methodology Response Surface Plot Response Variable Rotatability Rotatable Design Runs

S

Screening Second-Order Model Signal-to-Noise Ratio Significance Level Simple Linear Regression Single Factor Categorical Designs Square Plot Standard Order

T

Taguchi Designs/Robust Designs Three-Level Factorial Design.Two-Level Factorial Design Two-Way Design

U

Unbalanced Design Unblocked Design Unsaturated Model User-Defined Design

V

Variance Components Designs

Y

# A B C D E F G H I L M N O P R S T U V Y

Terms total # 118

Permanent link Design of Experiments - Modification date 2020-02-18 - Creation date 2019-12-15