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Course materials for PROBABILITY AND STATISTICS A/B
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PROBABILITY AND STATISTICS A/B

Course materials for PROBABILITY AND STATISTICS A/B

Teruo Nakatsuma (Faculty of Economics, Keio University, Japan)

How to set up Python and necessary packages

I strongly recommend using Anaconda. It can install Python along with numerous essential packages at once and allows us to manage those packages flexibly.

Step 1: Installing Anaconda

1. If you have an older Anaconda on your PC, uninstall it completely by folloiwng instructions.

2. Download an Anaconda installer (Windows, macOS or Linux) from here. Choose an installer for your OS.

3. Doubleclick the installer and follow the instructions on the screen. Do not change the default settings.

Step 2: Creating an environment

Start `Anaconda Powershell Prompt` (Windows) or `Terminal` (macOS, Linux) and type

``````conda update conda
``````

This will update conda (package manager) in Anaconda. Then type

``````conda create -n bayes -c conda-forge jupyterlab seaborn bokeh jupyter_bokeh pymc python-graphviz
``````

This will create the environment for PyMC. Then type

``````conda activate bayes
``````

and type

``````python -m ipykernel install --user --name bayes --display-name "Python (Bayes)"
``````

Now you are ready for Python!

1. Retry installation

If you encounter any errors during the installation process, go back to the default environment by typing

``````conda deactivate
``````

and remove `bayes` by typing

``````conda env remove -n bayes
``````

Then redo Step 2.

2. (macOS) Installing Command Line Tools for Xcode

In case the computer says `Command Line Tools for Xcode` is missing, install it as follows.

1. Install `Xcode` from App Store.

2. Start `Xcode`. If a pop-up window asks you to install additional tools, follow the instruction. Quit `Xcode`.

3. Start `Terminal` and install `Command Line Tools for Xcode` by typing

``````sudo xcode-select --install
``````

How to start Jupyter Notebook

Start `Anaconda Powershell Prompt` (Windows) or `Terminal` (macOS, Linux) and type

``````conda activate bayes
``````

Then type

``````jupyter notebook --port=8888
``````

Your default browser will pop up.

Alternatively, you may use JupyerLab by typing

``````jupyter lab --port=8888
``````

For a bokeh interactive plot to work properly, the Jupyter Notebook server must use `port 8888` which is set by default. In case this port is occupied by another Jupyter Notebook server, you need to stop it by typing

``````jupyter notebook stop
``````

before you open a new Jupyter Notebook. If this does not work, reboot your PC.

Jupyter Notebooks and related files in `notebook-a`

file name description
Cholera.csv London cholera pandemic data
Mroz.csv US women's labor participation data
StrikeDur.csv strikes duration data
USStocksSW.csv monthly US stock returns data
ar1_process.ipynb convergence of the AR(1) process
cholera.ipynb Bernoulli model of the cholera data
example_bernoulli.ipynb posterior inference on Bernoulli dist.
example_exponential.ipynb posterior inference on exponential dist.
example_normal.ipynb posterior inference on normal dist.
example_poisson.ipynb posterior inference on Poisson dist.
Housing.csv sales prices of houses
housing_price.ipynb hedonic price model of houses
labor_participation.ipynb logit model of labor participation
logit.ipynb PyMC example of logit model
poisson_regression.ipynb PyMC example of Poisson regression model
probit.ipynb PyMC example of probit model
prussian.csv Prussian army horse kick data
regression.ipynb PyMC example of regression analysis
ships_damage.ipynb Poisson regression model of ships damage
ships.csv ships damage data
wage_education.ipynb relationship between wage and education

Jupyter Notebooks and related files in `notebook-b`

file name description
bivariate_distribution.ipynb examples of bivariate distributions
large_sample.ipynb consistency and asymptotic normality
markovchain.ipynb Markov chain
probability_distribution.ipynb examples of probability distributions
python_introduction.ipynb simple example of Bayes' theorem
skewness_kurtosis.ipynb skewness and kurtosis

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