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Nº de artículo:
15402894
Applied Logistic Regression 3rd Edition
Nº de artículo:
15402894
GTQ 465
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Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables.
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What Stands Out
Comprehensive Coverage
This edition includes extensive topics on logistic regression applications, ensuring users gain in-depth knowledge and practical skills relevant for modern data analysis challenges.
Real-World Examples
Incorporates practical examples and case studies, allowing readers to relate theoretical concepts to real-life situations, enhancing understanding and applicability in various fields.
User-Friendly Approach
Designed for both beginners and experienced analysts, the structured layout and clear explanations make it accessible, promoting better learning and mastery of logistic regression techniques.
Detalles de producto
| Publisher | Wiley |
| Publication date | April 1, 2013 |
| Edition | 3rd |
| Language | English |
| Print length | 528 pages |
| ISBN-10 | 0470582472 |
| ISBN-13 | 978-0470582473 |
| Item Weight | 2.1 pounds (950 grams) |
| Dimensions | 6.25 x 1.2 x 9.3 inches (15.9 x 3 x 23.6 cm) |
Who Should Buy?
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Graduate Students
Ideal for graduate-level students studying statistics or data analysis, providing foundational knowledge in logistic regression techniques.
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Data Scientists
Useful for data scientists seeking to enhance their modeling skills, offering practical applications and examples in logistic regression.
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Statisticians
Beneficial for statisticians looking to deepen their understanding of logistic regression concepts and applications in various fields.
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Beginners
Not suitable for beginners without prior statistical knowledge, as it assumes familiarity with advanced statistical concepts.
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Applied Logistic Regression 3rd Edition
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Biostatistics Editorial Review
**** The "Applied Logistic Regression 3rd Edition" has garnered a positive reception among a diverse group of readers, ranging from students to seasoned professionals in various fields, particularly in analytics and statistics. Users appreciate the book for its comprehensive coverage of logistic regression methodologies, making it a vital resource for both academic and practical applications. Many reviewers note its accessibility, highlighting that even individuals with limited statistical backgrounds find the material engaging and relatively easy to understand. Feedback suggests that the book strikes a good balance between theory and application. Users have found the mathematical derivations insightful, yet effective in clarifying the practical utility of logistic regression models. The inclusion of numerous examples helps bridge the gap between complex concepts and real-world application, which many readers find beneficial in their professional endeavors, such as fundraising analytics and academic teaching. Despite its mathematical depth, some readers feel that certain sections may be overly technical. However, this has not significantly detracted from their overall positive experience with the content. Additionally, some reviewers have reported minor disappointments regarding the condition of their copies, but these issues appear to be overshadowed by the book's educational value. In summary, the "Applied Logistic Regression 3rd Edition" is well-regarded for its clarity, practical relevance, and ability to make complex statistical concepts accessible and enjoyable. It has undoubtedly earned its place in the libraries of both new learners and experienced practitioners in the field of statistics. **
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ventajas
- Comprehensive coverage of logistic regression methodologies.
- Accessible to readers with little statistical background.
- Engaging and enjoyable presentation of statistical concepts.
- Insightful mathematical derivations that clarify practical applications.
- Numerous examples that facilitate understanding.
Contras
- Some sections may be overly mathematical for certain readers.
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características y beneficios
- Comprehensive guide to logistic regression modeling.
- Focuses on applications in health sciences and beyond.
- Includes a chapter on analyzing correlated outcome data.
- Features rich datasets from real-world studies.
- Provides state-of-the-art techniques for model performance assessment.
- Ideal for professionals across diverse fields.
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