| Titre : |
Foundations of statistics for data scientists : with R and Python |
| Type de document : |
texte imprimé |
| Auteurs : |
Alan Agresti (1947-....) ; Maria Kateri |
| Editeur : |
Boca Raton, FL ; Londres : Chapman and Hall/CRC Press |
| Année de publication : |
2022 |
| Collection : |
Chapman & Hall/CRC Texts in statistical science  |
| Importance : |
xvii-467 p. |
| Présentation : |
fig., tabl. |
| Format : |
26 cm |
| ISBN/ISSN/EAN : |
978-0-367-74845-6 |
| Note générale : |
Bibliogr. p. 447-448. Index |
| Langues : |
Anglais (eng) |
| Descripteurs : |
Analyse mathématique , Classification , Distribution statistique , Échantillonnage , Inférence statistique Ensemble de méthodes permettant de tirer des conclusions fiables à partir de données d'échantillons statistiques , Langage informatique , Logiciel statistique R , Modèle linéaire
|
| Tags : |
Python Computer program language Quantitative research Langage de programmation |
| Index. décimale : |
211 Statistique mathématique |
| Résumé : |
This book is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. [Résumé éditeur] |
| En ligne : |
https://www.routledge.com/Foundations-of-Statistics-for-Data-Scientists-With-R-a [...] |
| Permalink : |
https://genes.bibli.fr/index.php?lvl=notice_display&id=170495 |
Foundations of statistics for data scientists : with R and Python [texte imprimé] / Alan Agresti (1947-....) ; Maria Kateri . - Boca Raton, FL ; Londres : Chapman and Hall/CRC Press, 2022 . - xvii-467 p. : fig., tabl. ; 26 cm. - ( Chapman & Hall/CRC Texts in statistical science) . ISBN : 978-0-367-74845-6 Bibliogr. p. 447-448. Index Langues : Anglais ( eng)
| Descripteurs : |
Analyse mathématique , Classification , Distribution statistique , Échantillonnage , Inférence statistique Ensemble de méthodes permettant de tirer des conclusions fiables à partir de données d'échantillons statistiques , Langage informatique , Logiciel statistique R , Modèle linéaire
|
| Tags : |
Python Computer program language Quantitative research Langage de programmation |
| Index. décimale : |
211 Statistique mathématique |
| Résumé : |
This book is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. [Résumé éditeur] |
| En ligne : |
https://www.routledge.com/Foundations-of-Statistics-for-Data-Scientists-With-R-a [...] |
| Permalink : |
https://genes.bibli.fr/index.php?lvl=notice_display&id=170495 |
|  |
Foundations of statistics for data scientists / Boca Raton, FL ; Londres : Chapman and Hall/CRC Press (2022)
