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Regression Techniques for Data Analysis / by Mike Nguyen

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Cham : Springer Nature Switzerland, 2026Publisher: Cham : Imprint: Springer, 2026Edition: 1st ed. 2026Description: 1 Online-Ressource(VIII, 670 p. 457 illus., 429 illus. in color.)ISBN:
  • 9783032018359
Subject(s): Additional physical formats: 9783032018342 | 9783032018366 | 9783032018373 | Erscheint auch als: 9783032018342 Druck-Ausgabe | Erscheint auch als: 9783032018366 Druck-Ausgabe | Erscheint auch als: 9783032018373 Druck-AusgabeDDC classification:
  • 519.536 23
DOI: DOI: 10.1007/978-3-032-01835-9Online resources: Summary: Linear Regression -- Non-linear regression -- Generalized linear models -- Linear mixed models -- Non-parametric regression.Summary: This volume explores regression analysis as the backbone of statistical modeling, offering readers a versatile and robust framework for analyzing relationships in data. From foundational linear models to more complex non-linear, generalized linear, mixed, and nonparametric approaches, this volume provides a comprehensive toolkit for real-world applications. Designed for both first-time learners and experienced analysts seeking a refresher, the book emphasizes model diagnostics, interpretation, and predictive accuracy. Its intuitive explanations, paired with hands-on examples, make it ideal for students studying for exams, professionals updating their skills, or researchers applying models in practice. With applications across marketing analytics, financial forecasting, and management science, this volume bridges theory and practice to support data-driven decision-making in diverse fields.PPN: PPN: 1961262401Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS
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