Causal Model Notes
Acknowledgement
1 Causal Models
2 Potential Outcomes
3 Matching
4 Task four : create sample distribution using bootsrapping
5 AB Testing
6 Difference-in-Differences (DiD) Methods
7 Synthetic Control Method (SCM)
- 7.1 AI Summary
8 Instrumental Variables (IV)
9 Regression Discontinuity Designs (RDD)
10 Fixed Effects and Panel Data Methods
- 10.1 Pooled Regression
- 10.2 Panel Data Methods
11 Ordinary Least Squares (OLS)
12 Resampling methods
- 12.1 Randomization-Based Methods
- 12.2 Bootstrapping
13 Hypotheis Testing
14 Maximum Likelihood Estimation
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Notes on Causal Models

Chapter 14 Maximum Likelihood Estimation

very nice website

[https://www.statlect.com/fundamentals-of-statistics/linear-regression-maximum-likelihood]