Mathematical Methods of Statistics
E933484
Mathematical Methods of Statistics is a foundational 1946 textbook that helped formalize modern mathematical statistics, particularly in the areas of probability theory and statistical inference.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Mathematical Methods of Statistics canonical | 2 |
How this entity was disambiguated
This entity first appeared as the object of triple T11560414 — 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: Mathematical Methods of Statistics Context triple: [Harald Cramér, notableWork, Mathematical Methods of Statistics]
-
A.
Foundations of the Theory of Probability
Foundations of the Theory of Probability is a landmark 1933 monograph that rigorously established modern probability theory on an axiomatic measure-theoretic basis.
-
B.
Soviet school of probability theory
The Soviet school of probability theory was a highly influential mathematical tradition that developed rigorous foundations and advanced methods in probability and stochastic processes, led by figures such as Kolmogorov, Khinchin, and their students.
-
C.
The Theory of Probability
The Theory of Probability is Hans Reichenbach’s influential philosophical and mathematical treatise that helped establish a rigorous, frequency-based interpretation of probability within the logical empiricist tradition.
-
D.
Neyman–Pearson theory of hypothesis testing
The Neyman–Pearson theory of hypothesis testing is a foundational statistical framework that formalizes how to construct and evaluate tests for competing hypotheses using concepts like Type I and Type II errors and power.
-
E.
Modern Probability Theory and Its Applications
"Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
- 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: Mathematical Methods of Statistics Target entity description: Mathematical Methods of Statistics is a foundational 1946 textbook that helped formalize modern mathematical statistics, particularly in the areas of probability theory and statistical inference.
-
A.
Foundations of the Theory of Probability
Foundations of the Theory of Probability is a landmark 1933 monograph that rigorously established modern probability theory on an axiomatic measure-theoretic basis.
-
B.
Soviet school of probability theory
The Soviet school of probability theory was a highly influential mathematical tradition that developed rigorous foundations and advanced methods in probability and stochastic processes, led by figures such as Kolmogorov, Khinchin, and their students.
-
C.
The Theory of Probability
The Theory of Probability is Hans Reichenbach’s influential philosophical and mathematical treatise that helped establish a rigorous, frequency-based interpretation of probability within the logical empiricist tradition.
-
D.
Neyman–Pearson theory of hypothesis testing
The Neyman–Pearson theory of hypothesis testing is a foundational statistical framework that formalizes how to construct and evaluate tests for competing hypotheses using concepts like Type I and Type II errors and power.
-
E.
Modern Probability Theory and Its Applications
"Modern Probability Theory and Its Applications" is a foundational textbook by Emanuel Parzen that systematically develops modern probability theory and demonstrates its use in a wide range of statistical and applied contexts.
- F. None of above. chosen
Statements (44)
| Predicate | Object |
|---|---|
| instanceOf |
monograph
ⓘ
statistics textbook ⓘ |
| academicDiscipline |
mathematics
ⓘ
statistics ⓘ |
| author | Harald Cramér NERFINISHED ⓘ |
| citedBy |
research articles in mathematical statistics
ⓘ
research articles in probability theory ⓘ |
| countryOfPublication |
United States of America
ⓘ
surface form:
United States
|
| describedAs |
classic work in probability and statistics
ⓘ
foundational textbook in mathematical statistics ⓘ |
| emphasis |
asymptotic methods in statistics
ⓘ
mathematical foundations of statistical methods ⓘ |
| field |
mathematical statistics
ⓘ
probability theory ⓘ statistical inference ⓘ |
| hasEdition | hardcover edition ⓘ |
| hasInfluenced |
development of modern mathematical statistics
ⓘ
probability theory education ⓘ theory of statistical inference ⓘ |
| inSeries | Princeton Mathematical Series NERFINISHED ⓘ |
| language | English ⓘ |
| notableFor |
formalization of statistical inference
ⓘ
influence on later statistics textbooks ⓘ systematic treatment of probability theory for statisticians ⓘ |
| publicationYear | 1946 ⓘ |
| publisher | Princeton University Press NERFINISHED ⓘ |
| structure | rigorous measure-theoretic approach to probability ⓘ |
| targetAudience |
advanced undergraduates in mathematics
ⓘ
graduate students in statistics ⓘ researchers in probability and statistics ⓘ |
| timePeriod | 20th century ⓘ |
| topic |
central limit theorem
NERFINISHED
ⓘ
characteristic functions ⓘ confidence intervals ⓘ estimation theory ⓘ hypothesis testing ⓘ large deviations ⓘ law of large numbers ⓘ limit theorems ⓘ maximum likelihood estimation ⓘ probability distributions ⓘ regression and correlation ⓘ sufficient statistics ⓘ |
| usedAs | graduate-level textbook ⓘ |
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: Mathematical Methods of Statistics Description of subject: Mathematical Methods of Statistics is a foundational 1946 textbook that helped formalize modern mathematical statistics, particularly in the areas of probability theory and statistical inference.
Referenced by (2)
Full triples — surface form annotated when it differs from this entity's canonical label.