share_book
Envoyer cet article par e-mail

An Introduction to Applied Multivariate Analysis with R (Use R!)

ou partager sur :

share_comment
Partager ce commentaire par e-mail

ou partager sur :

PRÊT A ACHETER?
(vous pouvez toujours annuler plus tard)


J'aime
An Introduction to Applied Multivariate Analysis with R (Use R!)

An Introduction to Applied Multivariate Analysis with R (Use R!)

  (Auteur),   (Auteur)


Prix : Cet article n'a pas encore de prix  ask_price

Demande de cotation sur ""
Ce titre est nouveau dans notre fonds d'ouvrages et nous ne l'avons encore jamais vendu à ce jour.
Notre engagement: Vous obtenir le meilleur prix
Aussi nombreux que soient les titres que nous référençons, absolument rien n'est automatisé dans la fixation de nos prix; et plutôt que de convertir automatiquement le prix en euros et risquer de répercuter sur vous un prix artificiellement élevé, nous vous faisons un devis rapide après avoir vérifié les prix auprès de nos différents fournisseurs.
Cette étape de demande de cotation est rapide (généralement quelques heures) et vise à vous faire bénéficier en permanence du meilleur prix pour vos achats de livres.


Sur commande

Des articles qui pourraient aussi vous intéresser

    Description de "An Introduction to Applied Multivariate Analysis with R (Use R!)"

    The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos.An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.

    Détails sur le produit

    • Reliure : Paperback
    • 288  pages
    • Dimensions :  2.0cmx15.5cmx23.1cm
    • Poids : 362.9g
    • Editeur :   Springer Paru le
    • Collection : Use R
    • ISBN :  1441996494
    • EAN13 :  9781441996497
    • Classe Dewey :  519.535
    • Langue : Anglais

    Commentaires sur cet article

    Personne n'a encore laissé de commentaire. Soyez le premier!

    Laisser un commentaire

    Rechercher des articles similaires par rayon

    Rechercher par thèmes associés

    The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos.An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.