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  • 1
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Springer
    UID:
    b3kat_BV047271212
    Format: 1 Online-Ressource (XVII, 228 p. 45 illus)
    Edition: 1st ed. 2021
    ISBN: 9783030675837
    Series Statement: Emerging Topics in Statistics and Biostatistics
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-67582-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-67584-4
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-030-67585-1
    Language: English
    Subjects: Computer Science
    RVK:
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    gbv_1756958629
    Format: 1 Online-Ressource (XVII, 228 Seiten)
    ISBN: 9783030675837
    Series Statement: Emerging topics in statistics and biostatistics
    Content: This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.
    Note: 1. Linear Regression -- 2. Introduction to Multi-Level Regression -- 3. Two-Level Multi-Level Modeling -- 4. Higher-Level Multi-Level Modeling -- 5. Longitudinal Data Analysis -- 6. Nonlinear Regression Modeling -- 7. Nonlinear Mixed-Effects Modeling -- 8. Generalized Linear Model -- 9. Generalized Multi-Level Model for Dichotomous Outcome -- 10. Generalized Multi-Level Model for Counts Outcome.
    Additional Edition: ISBN 9783030675820
    Additional Edition: ISBN 9783030675844
    Additional Edition: ISBN 9783030675851
    Additional Edition: Erscheint auch als Druck-Ausgabe Chen, Ding-Geng Statistical Regression Modeling with R Cham : Springer, 2021 ISBN 9783030675851
    Additional Edition: ISBN 9783030675820
    Language: English
    Subjects: Mathematics
    RVK:
    Keywords: Regressionsmodell
    URL: Cover
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    kobvindex_ZLB13345621
    Format: 1 Videokass. (98 Min.)
    Series Statement: Trigon Edition : [Video] 84
    Content: Ungewohnt lockeres Kino aus China, eine erfrischende Komödie aus Schanghai. In Form einer einfachen Ballade, ironisch erzählt, lehnt sich der Film an den Suzhou-Stil der traditionell gesungenen chinesischen Epen an. Baogen ist ein Mann vom Land mit bewährten Moralvorstellungen, der hart arbeitet, um sich ein neues städtisches Leben aufzubauen und um das Herz seiner scharfzüngigen Tante zu gewinnen. Eine wunderbare neue Welt wirft einen aufschlussreichen Blick auf das zeitgenössische, sich verändernde China und auf den Gegensatz und die Konfrontation von Materialismus, Kapitalismus, traditionellen Werten und menschlichem Begehren. Shi Run Jiu, ein 29jähriger Regisseur und Drehbuchautor, bringt mit seinem ersten Langspielfilm frischen Wind in den chinesischen Film. Er bringt uns zum Lachen und zwingt uns zugleich nachzudenken. Der ehrliche Bauer Baogen, der in die grosse Stadt kommt, um hier einen Preis abzuholen, den er in der Lotterie gewonnen hat, kommt ganz schön auf die Welt, denn die gewonnene Wohnung ist noch nicht einmal gebaut. Anstatt reich und berühmt zu werden, sieht er sich mit der simplen Realität konfrontiert. Er sucht bei seiner entfernten Verwandten Jinfang Unterschlupf und bringt deren Leben ganz schön durcheinander. Walter Ruggle (Trigon-Film)
    Note: Mandarin mit dt. und franz. Untertiteln
    Language: Chinese
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    gbv_1765980704
    Format: xvii, 228 Seiten , Illustrationen, Diagramme
    ISBN: 9783030675851 , 9783030675820
    Series Statement: Emerging Topics in Statistics and Biostatistics
    Content: 1. Linear Regression -- 2. Introduction to Multi-Level Regression -- 3. Two-Level Multi-Level Modeling -- 4. Higher-Level Multi-Level Modeling -- 5. Longitudinal Data Analysis -- 6. Nonlinear Regression Modeling -- 7. Nonlinear Mixed-Effects Modeling -- 8. Generalized Linear Model -- 9. Generalized Multi-Level Model for Dichotomous Outcome -- 10. Generalized Multi-Level Model for Counts Outcome.
    Content: This book provides a concise point of reference for the most commonly used regression methods. It begins with linear and nonlinear regression for normally distributed data, logistic regression for binomially distributed data, and Poisson regression and negative-binomial regression for count data. It then progresses to these regression models that work with longitudinal and multi-level data structures. The volume is designed to guide the transition from classical to more advanced regression modeling, as well as to contribute to the rapid development of statistics and data science. With data and computing programs available to facilitate readers' learning experience, Statistical Regression Modeling promotes the applications of R in linear, nonlinear, longitudinal and multi-level regression. All included datasets, as well as the associated R program in packages nlme and lme4 for multi-level regression, are detailed in Appendix A. This book will be valuable in graduate courses on applied regression, as well as for practitioners and researchers in the fields of data science, statistical analytics, public health, and related fields.
    Note: Literaturverzeichnis: Seite 223-224
    Additional Edition: ISBN 9783030675837
    Additional Edition: Erscheint auch als Online-Ausgabe Chen, Ding-Geng Statistical regression modeling with R Cham : Springer, 2021 ISBN 9783030675837
    Language: English
    Subjects: Mathematics
    RVK:
    Keywords: Regressionsmodell
    Library Location Call Number Volume/Issue/Year Availability
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