bayesian-statistical-analysis-using-python-part.json

{
  "alias": "video/2758/bayesian-statistical-analysis-using-python-part",
  "category": "SciPy 2014",
  "copyright_text": "https://www.youtube.com/t/terms",
  "description": "The aim of this course is to introduce new users to the Bayesian\napproach of statistical modeling and analysis, so that they can use\nPython packages such as NumPy, SciPy and\n`PyMC <https://github.com/pymc-devs/pymc>`__ effectively to analyze\ntheir own data. It is designed to get users quickly up and running with\nBayesian methods, incorporating just enough statistical background to\nallow users to understand, in general terms, what they are implementing.\nThe tutorial will be example-driven, with illustrative case studies\nusing real data. Selected methods will include approximation methods,\nimportance sampling, Markov chain Monte Carlo (MCMC) methods such as\nMetropolis-Hastings and Slice sampling. In addition to model fitting,\nthe tutorial will address important techniques for model checking, model\ncomparison, and steps for preparing data and processing model output.\nTutorial content will be derived from the instructor's book *Bayesian\nStatistical Computing using Python*, to be published by Springer in late\n2014.\n\n.. figure:: http://d.pr/i/pqWT+\n   :alt: PyMC forest plot\n\n   PyMC forest plot\n.. figure:: http://d.pr/i/AHZV+\n   :alt: DAG\n\n   DAG\n\nAll course content will be available as a GitHub repository, including\nIPython notebooks and example data.\n\nTutorial Outline\n----------------\n\n1. Overview of Bayesian statistics.\n2. Bayesian Inference with NumPy and SciPy\n3. Markov chain Monte Carlo (MCMC)\n4. The Essentials of PyMC\n5. Fitting Linear Regression Models\n6. Hierarchical Modeling\n7. Model Checking and Validation\n\nInstallation Instructions\n-------------------------\n\nThe easiest way to install the Python packages required for this\ntutorial is via\n`Anaconda <https://store.continuum.io/cshop/anaconda/>`__, a scientific\nPython distribution offered by Continuum analytics. Several other\ntutorials will be recommending a similar setup.\n\nOne of the key features of Anaconda is a command line utility called\n``conda`` that can be used to manage third party packages. We have built\na PyMC package for ``conda`` that can be installed from your terminal\nvia the following command:\n\n::\n\n    conda install -c https://conda.binstar.org/pymc pymc\n\nThis should install any prerequisite packages that are required to run\nPyMC.\n\nOne caveat is that conda does not yet have a build of PyMC for **Python\n3**. Therefore, you would have to build it yourself via pip:\n\n::\n\n    pip install git+git://github.com/pymc-devs/pymc.git@2.3\n\nFor those of you on Mac OS X that are already using the\n`Homebrew <http://brew.sh>`__ package manager, I have prepared a script\nthat will install the entire Python scientific stack, including PyMC\n2.3. You can download the script\n`here <https://gist.github.com/fonnesbeck/7de008b05e670d919b71>`__ and\nrun it via:\n\n::\n\n    sh install_superpack_brew.sh\n\n",
  "duration": null,
  "id": 2758,
  "language": "eng",
  "quality_notes": "",
  "recorded": "2014-07-09",
  "related_urls": [
    "http://brew.sh",
    "http://d.pr/i/AHZV+",
    "http://d.pr/i/pqWT+",
    "https://conda.binstar.org/pymc",
    "https://gist.github.com/fonnesbeck/7de008b05e670d919b71",
    "https://github.com/pymc-devs/pymc",
    "https://store.continuum.io/cshop/anaconda/"
  ],
  "slug": "bayesian-statistical-analysis-using-python-part",
  "speakers": [
    "Chris Fonnesbeck"
  ],
  "summary": "This hands-on tutorial will introduce statistical analysis in Python\nusing Bayesian methods. Bayesian statistics offer a flexible & powerful\nway of analyzing data, but are computationally-intensive, for which\nPython is ideal. As a gentle introduction, we will solve simple problems\nusing NumPy and SciPy, before moving on to Markov chain Monte Carlo\nmethods to build more complex models using PyMC.\n",
  "tags": [
    "bayesian",
    "statistics"
  ],
  "thumbnail_url": "https://i1.ytimg.com/vi/54sFjp7AvXM/hqdefault.jpg",
  "title": "Bayesian Statistical Analysis using Python - Part 3",
  "videos": [
    {
      "length": 0,
      "type": "youtube",
      "url": "https://www.youtube.com/watch?v=54sFjp7AvXM"
    }
  ]
}