{ "cells": [ { "cell_type": "markdown", "id": "e309e767", "metadata": {}, "source": [ "# Course Syllabus" ] }, { "cell_type": "code", "execution_count": 1, "id": "0fce9ea9", "metadata": { "tags": [ "remove_input", "remove_output" ] }, "outputs": [ { "data": { "text/plain": [ "'252 Chancellors Hall'" ] }, "metadata": { "scrapbook": { "mime_prefix": "", "name": "officeg" } }, "output_type": "display_data" }, { "data": { "text/plain": [ "'Spring 2024'" ] }, "metadata": { "scrapbook": { "mime_prefix": "", "name": "termg" } }, "output_type": "display_data" }, { "data": { "text/plain": [ "'rob.hicks@wm.edu'" ] }, "metadata": { "scrapbook": { "mime_prefix": "", "name": "emailg" } }, "output_type": "display_data" }, { "data": { "text/plain": [ "'MW 5:00-6:20 pm'" ] }, "metadata": { "scrapbook": { "mime_prefix": "", "name": "classtimeg" } }, "output_type": "display_data" }, { "data": { "text/plain": [ "'Tuesday 3:30 - 4:30pm'" ] }, "metadata": { "scrapbook": { "mime_prefix": "", "name": "officehoursg" } }, "output_type": "display_data" }, { "data": { "text/plain": [ "'219 Chancellors Hall'" ] }, "metadata": { "scrapbook": { "mime_prefix": "", "name": "classroomg" } }, "output_type": "display_data" }, { "data": { "text/plain": [ "'March 8'" ] }, "metadata": { "scrapbook": { "mime_prefix": "", "name": "midtermg" } }, "output_type": "display_data" } ], "source": [ "# set variables for this semester\n", "office = '252 Chancellors Hall'\t\t\n", "term = 'Spring 2024'\t\t\t\t\t\t\n", "email = 'rob.hicks@wm.edu'\t\t\t\n", "classtime = 'MW 5:00-6:20 pm'\t\n", "officehours = 'Tuesday 3:30 - 4:30pm'\n", "classroom = '219 Chancellors Hall'\n", "midterm = 'March 8' #'TBD' #'Feb 23' \n", "\n", "# set dates for this semester\n", "dates =\t [['First day of class',\t 'January 24 '], \n", "\t\t ['Spring Break',\t\t\t 'March 9-17'], \n", "\t\t ['Mid-Term Due',\t\t\t midterm], \n", " ['Last day of this class', 'May 1'], \n", "\t\t ['Final Project Due',\t 'May 7 (Midnight)']] \n", "\n", "from myst_nb import glue\n", "# put all data for this semester here\n", "glue(\"officeg\", office)\n", "glue(\"termg\", term)\n", "glue(\"emailg\", email)\n", "glue(\"classtimeg\", classtime)\n", "glue(\"officehoursg\", officehours)\n", "glue(\"classroomg\", classroom)\n", "glue(\"midtermg\", midterm)\n", "\n", "import pandas as pd\n", "df = pd.DataFrame(dates, columns=['Item', 'Date'])" ] }, { "cell_type": "markdown", "id": "25d022f5", "metadata": {}, "source": [ "- **Instructor**: Rob Hicks\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n", "- **Office**: {glue:text}`officeg`\n", "- **Term**: {glue:text}`termg`\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\n", "- **E-mail**: {glue:text}`emailg` \n", "- **Class Time**: {glue:text}`classtimeg` \n", "- **Class Room**: {glue:text}`classroomg`\n", "\n", "## Course Summary\n", "\n", "This course examines the use of Bayesian estimation methods for a wide\n", "variety of settings in applied economics. After a brief primer on\n", "Bayesian statistics, we will examine the use of the\n", "Metropolis-Hastings algorithm for parameter estimation via Markov\n", "Chain Monte Carlo methods. The student will write their own\n", "Metropolis-Hastings estimation algorithm for an ordinary least squares\n", "model. Building on this foundation, we will explore heirarchical and\n", "other models, and how they are implemented in Python PyMC.\n", "\n", "## Prerequisites\n", "\n", "ECON 308 (Econometrics) is required for this course. It is also\n", "*highly recommended* that you have had ECON 408 (Cross Section) or are\n", "willing to learn independently maximum likelihood estimation. It is\n", "also advantageous to have some programming skills and a working\n", "knowledge of linear algebra. This class is a very serious undertaking\n", "and if you aren't willing to go the extra mile and get up to speed, it\n", "will make for a long semester.\n", "\n", "## Software Resources\n", "\n", "There are various ways you can perform the modeling excercises for this\n", "course- all using `python` and the `pymc` package. These include\n", "\n", "- [`https://jupyterhub.wm.edu`](https://jupyterhub.wm.edu) and choosing the `SciPy with PyMC` image\n", "- `https://colab.google.com` and installing software to enable `pymc`\n", "- Running `anaconda python` on your own pc and installing software to enable `pymc`\n", "\n", "These are all acceptable to me provided your jupyter notebook executes on\n", "my computing environment (identical to `https://jupyterhub.wm.edu`).\n", "\n", "```{tip}\n", "Students are advised to use [`https://jupyterhub.wm.edu`](https://jupyterhub.wm.edu) with the `SciPy with PyMC` image.\n", "```\n", "\n", "Use of other software packages for Bayesian analysis (e.g. Stata,\n", "BUGS, Stan, etc.) is neither recommended or accepted without prior\n", "permission.\n", "\n", "## Important Dates\n", "\n", "
Item | \n", "Date | \n", "
---|---|
First day of class | \n", "January 24 | \n", "
Spring Break | \n", "March 9-17 | \n", "
Mid-Term Due | \n", "March 8 | \n", "
Last day of this class | \n", "May 1 | \n", "
Final Project Due | \n", "May 7 (Midnight) | \n", "