Introduction to Probability, Statistics & R : Foundations for Data-Based Sciences /
Finally, Part V focuses on advanced statistical modelling using simple and multiple regression and analysis of variance, laying the foundation for further studies in machine learning and data science applicable to various data and decision analytics contexts. Based on years of teaching experience, t...
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| Format: | Book |
| Language: | English |
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Springer International Publishing : Imprint: Springer,
2024
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| Edition: | 1st ed. 2024 |
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Table of Contents:
- Part I Introduction to basic Statistics and R
- 1 Introduction to basic statistics
- 2 Getting started with R
- Part II Introduction to Probability
- 3 Introduction to probability
- 4 Conditional probability and independence
- 5 Random variables and their probability distributions
- 6 Standard discrete distributions
- 7 Standard continuous distributions
- 8 Joint distributions and the CLT
- Part III Introduction to Statistical Inference
- 9 Introduction to statistical inference
- 10 Methods of point estimation
- 11 Interval estimation
- 12 Hypothesis testing
- Part IV Advanced Distribution Theory and Probability
- 13 Generating functions
- 14 Transformation and transformed distributions
- 15 Multivariate distributions
- 16 Convergence of estimators
- Part V Introduction to statistical modelling
- 17 Simple linear regression model
- 18 Multiple linear regression model
- 19 Analysis of variance
- Appendix: Table of common distributions