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Practical Multilevel Modeling Using R (Advanced Quantitative Techniques in the Social Sciences)
€ 100
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Practical Multilevel Modeling Using R provides students with a step-by-step guide for running their own multilevel analyses.
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Detaily produktu
| Publisher | SAGE Publications, Inc |
| Publication date | December 12, 2022 |
| Edition | 1st |
| Language | English |
| Print length | 256 pages |
| ISBN-10 | 1071846124 |
| ISBN-13 | 978-1071846124 |
| Item Weight | 15.9 ounces (450.77 grams) |
| Dimensions | 7 x 0.58 x 10 inches (17.8 x 1.5 x 25.4 cm) |
| Part of series | Advanced Quantitative Techniques in the Social Sciences |
Who Should Buy?
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Social Science Researchers
Ideal for researchers focusing on advanced statistical methods in social sciences and needing multilevel modeling techniques.
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Graduate Students
Great resource for graduate students studying statistics or data analysis, providing practical applications and insights into multilevel modeling.
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Data Analysts
Beneficial for data analysts in social research or policy evaluation looking to enhance their statistical modeling skills using R.
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Beginners in Statistics
Not suitable for those with little to no prior knowledge in statistics or R programming.
OPIS PRODUKTU
Practical Multilevel Modeling Using R (Advanced Quantitative Techniques in the Social Sciences)
Otázky a odpovede zákazníkov
-
otázka:
Is this book suitable for beginners?
odpoveď: Yes, it provides clear guidance and covers the basics of multilevel modeling. -
otázka:
Does it include practical examples?
odpoveď: Yes, the book includes real-world examples and a companion R package for application. -
otázka:
Are solutions to exercises available?
odpoveď: Yes, solutions for the 'Test Yourself' sections are available on the instructor website.
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Pros
- Comprehensive coverage of multilevel modeling
- Accessible for newcomers to R
- Includes practical examples
- Focuses on social science applications
Zápory
- Some concepts may be too advanced for beginners.
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Funkcie a výhody
- Step-by-step guide for multilevel analyses.
- Illustrates conceptual and statistical issues clearly.
- Annotated R syntax for practical application.
- Covers basics and advanced topics like diagnostics and power analysis.
- Designed for students in applied disciplines, not just methodologists.
- Includes 'Test Yourself' sections and a companion R package.
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