Econometrics-With-Python
Bayesian-Statistics-Econometrics
Econometrics-With-Python | Bayesian-Statistics-Econometrics | |
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1 | 1 | |
250 | 71 | |
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10.0 | 10.0 | |
over 1 year ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | MIT License |
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Econometrics-With-Python
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Python for Econometrics for Practitioners [Free Online Courses]
Econometrics with Python: This is a crash course for reviewing the most important concepts and techniques of econometrics. The theories are presented lightly without hustles of mathematical derivation and Python codes are mostly procedural and straightforward. Core concepts covered: multi- linear regression, logistic model, dummy variable, simultaneous equations model, panel data model and time series.
Bayesian-Statistics-Econometrics
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Python for Econometrics for Practitioners [Free Online Courses]
Bayesian Statistics with Python: Bayesian statistics is the last pillar of quantitative framework, also the most challenging subject. The course will explore the algorithms of Markov chain Monte Carlo (MCMC), specifically Metropolis-Hastings, Gibbs Sampler and etc., we will build up our own toy model from crude Python functions. In the meanwhile, we will cover the PyMC3, which is a library for probabilistic programming specializing in Bayesian statistics.
What are some alternatives?
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