Advanced modeling and data challenges / Mike Nguyen

• Autore: Nguyen, Mike
• Pubblicazione: Cham, : Springer, 2025
• Descrizione fisica: 1 testo elettronico (xiii, 449 p. : ill.)
• Soggetto topico: 62D10 - Missing data [MSC 2020]; 62F03 - Parametric hypothesis testing [MSC 2020]; 62F07 - Statistical ranking and selection procedures [MSC 2020]; 62F35 - Robustness and adaptive procedures (parametric inference) [MSC 2020]; 62M20 - Inference from stochastic processes and prediction; filtering [MSC 2020]; 62P05 - Applications of statistics to actuarial sciences and financial mathematics [MSC 2020]; 62P20 - Applications of statistics to economics [MSC 2020]; 62P25 - Applications of statistics to social sciences [MSC 2020]
• Soggetto non controllato: Data Collection; Data Interpretation; Hypothesis Testing; Latent Variable Models; Marginal Effects; Mediation; Missing data; Model selection; Model uncertainty; Moderation; Practical Analytics; Robust Statistics; Seasonality; Time series; Variable Selection
• Sommario/riassunto: This volume addresses the complexities of real-world data analysis, offering clear guidance through common challenges such as missing data, model specification, variable selection, and hypothesis testing. It also introduces tools for deeper interpretation—including marginal effects, interaction (moderation), and mediation analysis—to help uncover nuanced relationships in data. Ideal for both learners deepening their understanding and practitioners refining their techniques, this volume blends statistical theory with applied insight. Readers are equipped to navigate ambiguity, confront data imperfections, and extract actionable meaning. With practical examples and an emphasis on analytical reasoning, this book supports coursework, exam review, and professional development alike—making it an essential resource for building confidence in modern data analysis. (Dal sito dell'editore)
• Titolo autorizzato: Advanced Modeling and Data Challenges
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: VAN00310399
• Lo trovi qui: Univ. Vanvitelli
• Localizzazioni e accesso elettronico: https://doi.org/10.1007/978-3-032-01719-2