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Cleaning Up Your Act: Statistical Methods for Detecting Outliers in Regression

(Autor)

Buch | Softcover
128 Seiten
2024
tredition (Verlag)
978-3-384-27707-7 (ISBN)
CHF 39,85 inkl. MwSt
"Cleaning Up Your Act: Statistical Methods for Detecting Outliers in Regression" dives into the world of data analysis, specifically focusing on a crucial step: identifying outliers in regression models. Outliers are data points that fall far outside the expected pattern in your regression analysis. These outliers can distort your results and lead to misleading conclusions. This book equips you with various statistical methods to detect outliers effectively. You'll learn about Z-scores, interquartile ranges (IQRs), and other techniques to pinpoint these outliers. The book also delves into how to handle outliers, whether by removing them (if justified) or adjusting the model to account for their influence. By mastering these techniques, you'll ensure the accuracy and reliability of your regression analyses, leading to more dependable insights from your data. This book is ideal for researchers, analysts, and anyone who relies on regression modeling to make data-driven decisions.

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Erscheint lt. Verlag 2.7.2024
Verlagsort FINDAy
Sprache englisch
Maße 155 x 234 mm
Gewicht 227 g
Themenwelt Mathematik / Informatik Informatik Datenbanken
Mathematik / Informatik Mathematik Finanz- / Wirtschaftsmathematik
Wirtschaft Betriebswirtschaft / Management Allgemeines / Lexika
Schlagworte Bonferroni correction • Cook's Distance • Data Analysis • Dixon's Q-test • Grubbs' test • Influence diagnostics • Leverage scores • Outlier Detection • Regression Analysis • residual analysis • robust regression • Statistical Methods
ISBN-10 3-384-27707-4 / 3384277074
ISBN-13 978-3-384-27707-7 / 9783384277077
Zustand Neuware
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