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PA - C8 - MAP531 : Statistics

Domaine > Mathématiques appliquées.

Descriptif

Objectives

Statistics is the essence behind data science. It is clearly essential to have a deep understanding of the theory and the methods. This is a prerequisite before following a machine learning course.

 

Syllabus

  • Elements of decision theory: risk, loss, decision rules
  • Optimal decisions, unbiasedness, equivariance, sufficient statistics
  • Pointwise estimator: Z-estimator, M-estimator
  • Asymptotical results: law of large numbers, central limit theorem, consistency, asymptotic normality
  • Maximum likelihood, Fisher information, Kullback Leibler, asymptotic optimality
  • Tests: definitions, the Neyman-Pearson lemma, Uniformly Most Powerful test, p-value

Langue du cours : Anglais

Diplôme(s) concerné(s)

Parcours de rattachement

Format des notes

Numérique sur 20

Littérale/grade réduit

Pour les étudiants du diplôme Data Science for Business

Le rattrapage est autorisé
    L'UE est acquise si note finale transposée >= C
    • Crédits ECTS acquis : 4 ECTS
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