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Exercise Book of Statistical Inference / by Francesca Gasperoni, Francesca Ieva, Anna Maria Paganoni.
Springer Nature - Springer Mathematics and Statistics (R0) eBooks 2025 English International Available online
Springer Nature - Springer Mathematics and Statistics (R0) eBooks 2025 English International- Format:
- Book
- Author/Creator:
- Gasperoni, Francesca.
- Series:
- La Matematica per il 3+2, 2038-5757 ; 173
- Language:
- English
- Subjects (All):
- Statistics.
- Probabilities.
- Mathematics.
- Statistical Theory and Methods.
- Probability Theory.
- Local Subjects:
- Statistical Theory and Methods.
- Probability Theory.
- Mathematics.
- Physical Description:
- 1 online resource (346 pages)
- Edition:
- 1st ed. 2025.
- Place of Publication:
- Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
- Summary:
- This book was created with the goal of helping students transition from the theoretical and methodological concepts of statistical inference to their implementation on a computer. The first part of the book is primarily focused on exercises to be solved with pen and paper, so that students can apply knowledge derived from lemmas and theorems; while the second part consists of labs, which involve both the manual implementation of algorithms and the learning of built-in tools for efficient analysis of datasets derived from real-world problems. To optimize the understanding of the topics developed and to guide the reader through their studies, the book is organized into chapters, each of which includes an introductory section that reviews the theoretical foundations of statistical inference, followed by a second part with exercises, each accompanied by a comprehensive solution on paper and, when appropriate, using software. This book is aimed at undergraduate students in Statistics, Mathematics, Engineering, and for graduate-level courses in Data Science.
- Contents:
- Part I: Statistical Inference
- 1 Fundamentals of Probability and Statistics
- 2 Sufficient, Minimal, and Complete Statistics
- 3 Point Estimators
- 4 Uniform Minimum Variance Unbiased Estimators (UMVUEs)
- 5 Likelihood Ratio Test
- 6 Uniformly Most Powerful Test
- 7 Confidence Intervals
- 8 Asymptotic Statistics
- Part II: Regression Models and Analysis of Variance
- 9 Linear Regression
- 10 Generalized Linear Models
- 11 ANOVA: Analysis of Variance
- 12 Summary Exercises
- Appendix A: Probability Distributions.
- ISBN:
- 3-031-86670-3
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