maximum likelihood: meaning, definition, pronunciation and examples

C1-C2 (Specialized)
UK/ˌmæk.sɪ.məm ˈlaɪk.li.hʊd/US/ˌmæk.sə.məm ˈlaɪk.li.hʊd/

Technical/Academic

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Quick answer

What does “maximum likelihood” mean?

In statistics and probability theory, the method or principle of selecting the parameter values of a model that make the observed data most probable.

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Pronunciation

Definition

Meaning and Definition

In statistics and probability theory, the method or principle of selecting the parameter values of a model that make the observed data most probable.

A fundamental approach to parameter estimation and model fitting, central to frequentist inference, where the 'best' explanation is the one that maximizes the probability of the observed outcomes under the assumed model.

Dialectal Variation

British vs American Usage

Differences

No significant difference in meaning or usage. Spelling of related terms may follow regional conventions (e.g., 'parameterise' vs. 'parameterize').

Connotations

Neutral, technical term in both varieties.

Frequency

Equally common in academic and professional statistics contexts in both the UK and US.

Grammar

How to Use “maximum likelihood” in a Sentence

The maximum likelihood of [NOUN PHRASE] is...We estimated the parameters via maximum likelihood.To calculate/find/determine the maximum likelihood...The maximum likelihood estimator for [PARAMETER]...

Vocabulary

Collocations

strong
maximum likelihood estimationmaximum likelihood estimatormaximum likelihood methodprinciple of maximum likelihoodcompute the maximum likelihood
medium
maximum likelihood approachmaximum likelihood frameworkmaximum likelihood analysisbased on maximum likelihoodderive the maximum likelihood
weak
maximum likelihood valuemaximum likelihood solutionmaximum likelihood resultapply maximum likelihooduse maximum likelihood

Examples

Examples of “maximum likelihood” in a Sentence

verb

British English

  • The parameters were maximum-likelihooded using an iterative algorithm.
  • We need to maximum-likelihood this model.

American English

  • The parameters were maximum-likelihooded using specialized software.
  • They maximum-likelihooded the regression coefficients.

adverb

British English

  • The parameters were estimated maximum-likelihoodly.
  • The model was fitted maximum-likelihoodly.

American English

  • The coefficients were derived maximum-likelihoodly.
  • It was optimised maximum-likelihoodly.

adjective

British English

  • The maximum-likelihood estimates were computed.
  • They performed a maximum-likelihood analysis.

American English

  • The maximum-likelihood estimator is consistent.
  • This is the maximum-likelihood solution.

Usage

Meaning in Context

Business

Rare, except in highly quantitative fields like econometrics or data science for predictive modeling.

Academic

Core term in statistics, econometrics, machine learning, biostatistics, and any field using quantitative model fitting.

Everyday

Virtually never used.

Technical

Standard, foundational term in statistics, data science, and engineering for parameter estimation.

Vocabulary

Synonyms of “maximum likelihood”

Strong

MLE (acronym)

Neutral

most probable estimateoptimal parameter estimate

Weak

likelihood maximizationbest-fit estimate

Vocabulary

Antonyms of “maximum likelihood”

method of momentsBayesian estimationleast squares estimation

Watch out

Common Mistakes When Using “maximum likelihood”

  • Using 'maximum likelihood' as an adjective without a following noun (e.g., 'We used maximum likelihood' is correct; 'We used the maximum likelihood method' is clearer).
  • Confusing 'maximum likelihood estimator' (the rule/formula) with 'maximum likelihood estimate' (the numerical result).

FAQ

Frequently Asked Questions

No. Probability refers to the chance of data given known parameters. Likelihood refers to the 'plausibility' of parameters given observed data. Maximum likelihood finds the parameters that maximize this plausibility.

It is ubiquitous in statistical model fitting, including regression, machine learning (e.g., logistic regression, neural networks trained with cross-entropy loss), econometrics, and biological sciences.

Common alternatives include Bayesian methods (which incorporate prior beliefs), the method of moments, and least squares estimation (which is equivalent to MLE under normality assumptions).

Yes, maximum likelihood estimators can be biased, especially in small samples, though they often have good properties like consistency and asymptotic efficiency.

In statistics and probability theory, the method or principle of selecting the parameter values of a model that make the observed data most probable.

Maximum likelihood is usually technical/academic in register.

Maximum likelihood: in British English it is pronounced /ˌmæk.sɪ.məm ˈlaɪk.li.hʊd/, and in American English it is pronounced /ˌmæk.sə.məm ˈlaɪk.li.hʊd/. Tap the audio buttons above to hear it.

Learning

Memory Aids

Mnemonic

Think of a detective: among all possible suspects (parameter values), they choose the one whose story makes the observed evidence (data) most LIKELY.

Conceptual Metaphor

PARAMETER CHOICE IS PATHFINDING (finding the peak of the likelihood 'mountain').

Practice

Quiz

Fill in the gap
In classical statistics, the estimator is often preferred for its desirable asymptotic properties.
Multiple Choice

What does 'maximum likelihood estimation' fundamentally aim to do?

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