Objectifs :
This module aims to give the basics of classical statistical analysis by means of examples, without going into the details of theoretical formulations.
Beginning with descriptive statistics, we develop hypothesis tests on these statistics and their comparison between different samples.
We also present the analysis of variance and regression methods on quantitative and qualitative variables. T

Learn to perform statistical analysis on data.
Perform empirical hypothesis testing.
Perform and interpret linear and logistic regressions.

Programme :
1. Descriptive statistics (mean, variance, standard deviation, median, quartiles, deciles, skewness, kurtosis, covariance, correlation)
2. Hypothesis testing on proportion, mean, variance or correlation
3. Comparisons of several means: analysis of variance

Pré-requis :
English speaking, use of Excel spreadsheet.

Méthode pédagogique :
Based on examples using common software (Excel) or statistics (R, Stata, SAS, …)
Bibliography: Paul NEWBOLD, William L. CARLSON and Betty THORNE (2019): Statistics for Business and Economics (9th edition), Pearson Education.

Compétences acquises à l'issue de la formation :
Ability to perform a basic statistical analysis on data.

Les Compétences et capacités visées à l'issue de la formation (fiches RNCP)

Arrêté du 22 février 2019 définissant les compétences des diplômés du doctorat et inscrivant le doctorat au répertoire national de la certification professionnelle. https://www.legifrance.gouv.fr/loda/id/JORFTEXT000038200990/

Bloc 4 : Veille scientifique et technologique à l’échelle internationale

- Acquérir, synthétiser et analyser les données et informations scientifiques et technologiques d’avant-garde à l’échelle internationale

La formation participe à l'objectif suivant :conforter la culture scientifique des doctorants dans leur champ disciplinaire ou en interdisciplinaire