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91878442
A First Course in Causal Inference (Chapman & Hall/CRC Texts in Statistical Science)
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Item #:
91878442
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What Stands Out
Comprehensive Coverage
This book offers an extensive introduction to causal inference, making complex concepts accessible to beginners while also providing depth for advanced readers, ensuring a thorough understanding of the subject.
Practical Applications
Includes real-world examples and case studies that demonstrate how causal inference techniques can be effectively applied in various fields, aiding readers in translating theory into practice.
Expert Authorship
Authored by leading experts in statistical science, the text guarantees high-quality insights and methodologies, positioning itself as a reliable resource for students and practitioners alike.
Product Details
| Publisher | Chapman and Hall/CRC |
| Publication date | June 7, 2024 |
| Edition | 1st |
| Language | English |
| Print length | 448 pages |
| ISBN-10 | 1032758627 |
| ISBN-13 | 978-1032758626 |
| Item Weight | 2.15 pounds (980 grams) |
| Dimensions | 7.24 x 1.2 x 10.24 inches (18.4 x 3 x 26 cm) |
| Part of series | Miller Williams Poetry Prize |
Who Should Buy?
-
Statistics Students
Ideal for undergraduate and graduate students seeking to understand causal inference methodologies and their applications in statistics.
-
Data Analysts
Provides data analysts with foundational knowledge on causal inference techniques, essential for meaningful interpretation of data findings.
-
Researchers
Beneficial for researchers in social sciences, providing tools to analyze relationships and influence between variables effectively.
-
Beginners in Statistics
Not suitable for complete beginners, as it assumes a basic understanding of statistical concepts and methodologies.
Product Description
A First Course in Causal Inference (Chapman & Hall/CRC Texts in Statistical Science)
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Pros
- Comprehensive causal inference coverage
- User-friendly explanations and examples
- Strong theoretical foundation
- Diverse statistical methodologies included
- Suitable for beginners and experts
Cons
- Occasional complex notation
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