The Design of Experiments
E212225
The Design of Experiments is a foundational statistics book by Ronald A. Fisher that established modern principles and methods for planning and analyzing scientific experiments.
All labels observed (4)
| Label | Occurrences |
|---|---|
| The Design of Experiments canonical | 3 |
| Confounding in Factorial Experiments | 1 |
| The Arrangement of Field Experiments | 1 |
| The Simple Factorial Experiment | 1 |
How this entity was disambiguated
This entity first appeared as the object of triple T1908304 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Design of Experiments Context triple: [Ronald A. Fisher, notableWork, The Design of Experiments]
-
A.
Gaussian law of error
The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
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B.
“Statistical Confluence Analysis by Means of Complete Regression Systems”
“Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
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C.
Some Considerations Touching the Usefulness of Experimental Natural Philosophy
Some Considerations Touching the Usefulness of Experimental Natural Philosophy is a 17th-century work by Robert Boyle that defends and promotes the value of experimental methods in the study of nature.
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D.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
-
E.
Laplace law of error
The Laplace law of error is a probability distribution characterized by a sharp peak at the mean and heavier tails than the normal distribution, historically used to model the magnitude of observational errors.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: The Design of Experiments Target entity description: The Design of Experiments is a foundational statistics book by Ronald A. Fisher that established modern principles and methods for planning and analyzing scientific experiments.
-
A.
Gaussian law of error
The Gaussian law of error is a fundamental statistical principle stating that measurement errors tend to follow a normal (bell-shaped) distribution, forming the basis of much of probability theory and statistical inference.
-
B.
“Statistical Confluence Analysis by Means of Complete Regression Systems”
“Statistical Confluence Analysis by Means of Complete Regression Systems” is a foundational econometric work by Ragnar Frisch that develops a systematic regression-based framework for analyzing interdependent economic relationships.
-
C.
Some Considerations Touching the Usefulness of Experimental Natural Philosophy
Some Considerations Touching the Usefulness of Experimental Natural Philosophy is a 17th-century work by Robert Boyle that defends and promotes the value of experimental methods in the study of nature.
-
D.
A Solution to the Ecological Inference Problem
A Solution to the Ecological Inference Problem is a influential methodological book by political scientist Gary King that introduces statistical techniques for inferring individual-level behavior from aggregate data.
-
E.
Laplace law of error
The Laplace law of error is a probability distribution characterized by a sharp peak at the mean and heavier tails than the normal distribution, historically used to model the magnitude of observational errors.
- F. None of above. chosen
Statements (48)
| Predicate | Object |
|---|---|
| instanceOf |
book
ⓘ
non-fiction book ⓘ statistics book ⓘ |
| author |
R. A. Fisher
ⓘ
linked to:
Ronald A. Fisher
Ronald A. Fisher ⓘ |
| coreConcept |
local control of error
ⓘ
randomization principle ⓘ replication principle ⓘ |
| countryOfOrigin | United Kingdom ⓘ |
| describes | principles of experimental design ⓘ |
| field |
experimental design
ⓘ
statistics ⓘ |
| firstEditionYear | 1935 ⓘ |
| hasEdition |
fifth edition
ⓘ
fourth edition ⓘ second edition ⓘ seventh edition ⓘ sixth edition ⓘ third edition ⓘ |
| hasNotableChapter |
Confounding in Factorial Experiments
ⓘ
linked to:
The Design of Experiments
The Arrangement of Field Experiments ⓘ
linked to:
The Design of Experiments
The Generalization of Factorial Design ⓘ The Principles of Experimentation ⓘ The Simple Factorial Experiment ⓘ
linked to:
The Design of Experiments
The Theory of Confounding ⓘ The Transformation of Data ⓘ |
| influenced |
applied statistics
ⓘ
modern experimental design ⓘ |
| introducesConcept |
Latin square design
ⓘ
completely randomized design ⓘ confounded factorial design ⓘ factorial design ⓘ randomized block design ⓘ randomized design ⓘ |
| language | English ⓘ |
| publicationYear | 1935 ⓘ |
| publisher | Oliver and Boyd ⓘ |
| topic |
agricultural experiments
ⓘ
analysis of variance ⓘ blocking ⓘ confounding ⓘ error estimation ⓘ factorial experiments ⓘ randomization ⓘ replication ⓘ |
| usedIn |
agricultural research
ⓘ
industrial experimentation ⓘ scientific research ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: The Design of Experiments Description of subject: The Design of Experiments is a foundational statistics book by Ronald A. Fisher that established modern principles and methods for planning and analyzing scientific experiments.
Referenced by (6)
Full triples — surface form annotated when it differs from this entity's canonical label.
linked to: The Design of Experiments
linked to: The Design of Experiments
linked to: The Design of Experiments