Academic Journal
Statistics for Data Science (using R)
| Τίτλος: | Statistics for Data Science (using R) |
|---|---|
| Συγγραφείς: | Palarea Albaladejo, Javier |
| Πηγή: | Materials i objectes docents |
| Στοιχεία εκδότη: | Universitat de Girona. Departament d'Informàtica, Matemàtica aplicada i Estadística |
| Έτος έκδοσης: | 2024 |
| Συλλογή: | MDX (Learning Materials Online) |
| Θεματικοί όροι: | Estadística -- Informàtica, Statistics -- Data processing, Anàlisi multivariable -- Informàtica, Multivariate analysis -- Data processing, R (Llenguatge de programació), R (Computer program language), R (Llenguatge de programació) -- Problemes, exercicis, etc, R (Computer program language) -- Problems, exercises |
| Περιγραφή: | These course notes provide an applied introduction to multivariate data analysis methods and statistical models using the R system for statistical computing. Currently, they are primarily aimed at students of the “Statistics for Data Science” course of the MSc in Data Science of the University of Girona and it serves as basis to more specialised courses taught later on. They build on previous materials developed by the author while delivering training courses for scientists at Biomathematics and Statistics Scotland (BioSS) and lecturing the Multivariate Data Analysis course at the University of Edinburgh. Basic statistical knowledge and some experience working and managing data in the R environment is assumed. The course avoids mathematical/statistical theory as much as possible and concentrates on the underlying concepts, emphasising how to put them in practice using R as computing tool.They are divided into two blocks:Chapters 1-6: overview of some multivariate methods aimed at data dimension reduction, classification, identification of similarities, associations, and patters in data sets; with a focus on data exploration and graphical representation. Chapters 7-12: overview of some of the families of linear, non-linear, generalised linear and additive regression models commonly used in statistical modelling, including questions related to model validation, variable selection and dealing with high dimensions |
| Τύπος εγγράφου: | text |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| Relation: | http://hdl.handle.net/10256/24695 |
| Διαθεσιμότητα: | http://hdl.handle.net/10256/24695 |
| Rights: | Tots els drets reservats ; info:eu-repo/semantics/openAccess |
| Αριθμός Καταχώρησης: | edsbas.2A85545F |
| Βάση Δεδομένων: | BASE |
| FullText | Text: Availability: 0 CustomLinks: – Url: http://hdl.handle.net/10256/24695# Name: EDS - BASE (ns324271) Category: fullText Text: View record from BASE |
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| Items | – Name: Title Label: Title Group: Ti Data: Statistics for Data Science (using R) – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Palarea+Albaladejo%2C+Javier%22">Palarea Albaladejo, Javier</searchLink> – Name: TitleSource Label: Source Group: Src Data: Materials i objectes docents – Name: Publisher Label: Publisher Information Group: PubInfo Data: Universitat de Girona. Departament d'Informàtica, Matemàtica aplicada i Estadística – Name: DatePubCY Label: Publication Year Group: Date Data: 2024 – Name: Subset Label: Collection Group: HoldingsInfo Data: MDX (Learning Materials Online) – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Estadística+--+Informàtica%22">Estadística -- Informàtica</searchLink><br /><searchLink fieldCode="DE" term="%22Statistics+--+Data+processing%22">Statistics -- Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Anàlisi+multivariable+--+Informàtica%22">Anàlisi multivariable -- Informàtica</searchLink><br /><searchLink fieldCode="DE" term="%22Multivariate+analysis+--+Data+processing%22">Multivariate analysis -- Data processing</searchLink><br /><searchLink fieldCode="DE" term="%22R+%28Llenguatge+de+programació%29%22">R (Llenguatge de programació)</searchLink><br /><searchLink fieldCode="DE" term="%22R+%28Computer+program+language%29%22">R (Computer program language)</searchLink><br /><searchLink fieldCode="DE" term="%22R+%28Llenguatge+de+programació%29+--+Problemes%22">R (Llenguatge de programació) -- Problemes</searchLink><br /><searchLink fieldCode="DE" term="%22exercicis%22">exercicis</searchLink><br /><searchLink fieldCode="DE" term="%22etc%22">etc</searchLink><br /><searchLink fieldCode="DE" term="%22R+%28Computer+program+language%29+--+Problems%22">R (Computer program language) -- Problems</searchLink><br /><searchLink fieldCode="DE" term="%22exercises%22">exercises</searchLink> – Name: Abstract Label: Description Group: Ab Data: These course notes provide an applied introduction to multivariate data analysis methods and statistical models using the R system for statistical computing. Currently, they are primarily aimed at students of the “Statistics for Data Science” course of the MSc in Data Science of the University of Girona and it serves as basis to more specialised courses taught later on. They build on previous materials developed by the author while delivering training courses for scientists at Biomathematics and Statistics Scotland (BioSS) and lecturing the Multivariate Data Analysis course at the University of Edinburgh. Basic statistical knowledge and some experience working and managing data in the R environment is assumed. The course avoids mathematical/statistical theory as much as possible and concentrates on the underlying concepts, emphasising how to put them in practice using R as computing tool.They are divided into two blocks:Chapters 1-6: overview of some multivariate methods aimed at data dimension reduction, classification, identification of similarities, associations, and patters in data sets; with a focus on data exploration and graphical representation. Chapters 7-12: overview of some of the families of linear, non-linear, generalised linear and additive regression models commonly used in statistical modelling, including questions related to model validation, variable selection and dealing with high dimensions – Name: TypeDocument Label: Document Type Group: TypDoc Data: text – Name: Format Label: File Description Group: SrcInfo Data: application/pdf – Name: Language Label: Language Group: Lang Data: English – Name: NoteTitleSource Label: Relation Group: SrcInfo Data: http://hdl.handle.net/10256/24695 – Name: URL Label: Availability Group: URL Data: http://hdl.handle.net/10256/24695 – Name: Copyright Label: Rights Group: Cpyrght Data: Tots els drets reservats ; info:eu-repo/semantics/openAccess – Name: AN Label: Accession Number Group: ID Data: edsbas.2A85545F |
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| RecordInfo | BibRecord: BibEntity: Languages: – Text: English Subjects: – SubjectFull: Estadística -- Informàtica Type: general – SubjectFull: Statistics -- Data processing Type: general – SubjectFull: Anàlisi multivariable -- Informàtica Type: general – SubjectFull: Multivariate analysis -- Data processing Type: general – SubjectFull: R (Llenguatge de programació) Type: general – SubjectFull: R (Computer program language) Type: general – SubjectFull: R (Llenguatge de programació) -- Problemes Type: general – SubjectFull: exercicis Type: general – SubjectFull: etc Type: general – SubjectFull: R (Computer program language) -- Problems Type: general – SubjectFull: exercises Type: general Titles: – TitleFull: Statistics for Data Science (using R) Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Palarea Albaladejo, Javier IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2024 Identifiers: – Type: issn-locals Value: edsbas – Type: issn-locals Value: edsbas.oa Titles: – TitleFull: Materials i objectes docents Type: main |
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