Keita, Moussa (2016): Introduction à la méthode statistique et probabiliste.
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Abstract
This manuscript provides an introduction to statistics and probability method. It is structured around three themes developed in five chapters. The first part is an introduction to probability calculations in which we introduce the notions of elementary probability, probabilized spaces, random variables, distribution et density functions. We also review the main probability laws that characterize the common phenomenas of observation. The second part is an introduction to statistical analytical approaches. In this part, we present, one hand, the descriptive and exploratory methods and on other hand the inferential methods. The notions discussed in this section are statistical distributions, links between variables, estimators and hypothesis testing. As for the third part, it provides an introduction to survey techniques centered on the study of sampling protocols and estimations methods for extrapolation.
Item Type: | MPRA Paper |
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Original Title: | Introduction à la méthode statistique et probabiliste |
English Title: | Introduction to statistical and probabilistic method |
Language: | French |
Keywords: | statistics, probabilities, estimators, survey |
Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C10 - General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C12 - Hypothesis Testing: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C18 - Methodological Issues: General |
Item ID: | 69824 |
Depositing User: | Moussa keita |
Date Deposited: | 03 Mar 2016 12:58 |
Last Modified: | 26 Sep 2019 10:25 |
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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/69824 |