Mastering Statistics with R
Welcome
Part I: Foundations
1 Probability Concept
2 Elementary Statistics
3 Mathematical Statistics
- 3.1 Limiting Distributions
  - 3.1.1 Converge in probability
  - 3.1.2 Converge in distribution
Part II: Methodology - Beginner
4 Probability Models
5 Regression Analysis
6 Categorical Data Analysis
7 Multivariate Analysis
8 Time Series Analysis
Part III: Methodology - Advanced
9 Generalized Linear Models
10 Spatial Statistics
11 Functional Data Analysis
12 Bayesian Analysis
- 12.1 Laplace Approximation and BIC
13 High Dimensional Data
Part IV: Methodology - Others
14 Non-parametric model
15 Extreme value theory
16 Directional Statistics
- 16.1 Circular Regression
17 Topological Data Analysis
Part V: Application - Industrial Statistics
18 Quality Control
19 Reliability Analysis
20 Design of Experiments
Part VI: Application - Biostatistic
21 Biostatistical Data Analysis
22 Survial Analysis
23 Causal Inference
- 23.1 DAG
24 Statistical Designs and Analyses in Clinical Trials
Part VII: Application - Others
25 Financial Statistics
26 Social Statistics
- 26.1 Human Behaviour
- 26.2 Sport
27 Psychometrics
- 27.1 Item Response Theory
Part VIII: Computational Statistics
28 Statistical Learning
29 Statistical Computing
30 Advanced Machine Learning
31 Deep Learning
Part IX: Computer Science Skills
32 Data Structure and Algorithm
- 32.1 Data Structure
- 32.2 Algorithm
  - 32.2.1 Graph and tree traversal algorithms
33 Information Theory
- 33.1 Entropy
- 33.2 Data compression
34 Big Data Analytics Techniques and Applications
35 Multimodal Data Analysis
Part X: Data Communication
36 Data Processing
- 36.1 Data Collection
- 36.2 Data Preprocessing
37 Data Visualization
38 Data Mining
- 38.1 Association rule learning
- 38.2 Anomaly detection
39 Statistical Consulting
Part XI: Data Integration
40 Data Management
41 DataOps
42 Meta Analysis
- 42.1 Federated Learning
Part XII: Statistic Theory
43 Statistical Inference
- 43.1 Frequentist inference
- 43.2 Bayesian inference
44 Decision Theory
- 44.1 Regret
45 Probability Theory
46 Algebraic Statistics
47 Free Probability Theory
Part VIII: Miscellaneous
48 Statistical Education
49 Ethics and Philosophy
- 49.1 Differential Privacy
Appendix
A Matrix calculus
B Advanced programming in R
Published with bookdown

Mastering Statistics with R

43.1 Frequentist inference

For graduate students

Exponential family

Calculate the power (non-central Chi-square)

Large sample theory