Course Overview

The overview includes an introduction to the course, guidelines on grading, and required texts.

Introduction

This course is the first of a three semester series of courses designed to introduce you to the practice of research, particularly the applied side of quantitative research. The goal of this course to help you to prepare a paper that can be presented at a major research conference and, hopefully, submitted to a journal for publication.

To accomplish this goal, you will choose from among publicly available datasets. You will identify a research topic, then later a research question. You will create a dataset using the NCES survey and other publicly available sources. By the end of the semester, you will have a properly formatted and cleaned dataset, with auxiliary information from other sources included. Next semester we will analyze this dataset. By the end of May, you will complete a paper based on this analysis.

Along the way, you will develop skills that will be helpful in future work using any kind of data. This class has a strong emphasis on using programming skills to aid in the replication of work and to simplify complex analyses.

Grading

Assignments

There will be a total of eleven assignments, which will be graded pass/fail. All assignments, unless otherwise stated, are due by midnight of the evening before the next class. Late assignments will not be accepted. These assignments will account for half of your grade. Collaboration on assignments is fine, though many of the assignments will ask you to work with variables and datasets of your own choosing.

TOTAL: 50%

Summary Paper and Codebook

At the end of the semester, you will need to present the results of your data collection efforts, with a summary paper of no more than five pages of text, accompanied by properly formatted tables and graphics. The summary paper and codebook will be due on December

You will present your work to the rest of the class on December 9.

TOTAL: 50%

Recommended Texts

Baum, C. (2006). An Introduction to Modern Econometrics Using STATA. College Station: STATA Press
Long, J.S. (2009). The Workflow of Data Analysis Using Stata. College Station: STATA Press

For this semester, both of these books are optional. I may recommend a few chapters from both as the semester progresses, but the class notes are the only required reading.

Software

You need to have access to a working version of Stata 14. Stata is installed on computers on Peabody campus, including our classroom (Wyatt 130), and on stations in the Peabody library. You are not required to purchase Stata, but you will need to use it for class assignments. I strongly recommend, however, that you purchase it.

If you do purchase Stata, you will need at least Stata IC. Vanderbilt has what’s called a gradplan with Stata under which you can purchase the software at greatly reduced prices. Stata SE is a more powerful version of Stata that is useful for the larger datasets many of you may be working with.

Submission of work

Unless given other instructions, all assignment files should be submitted with the following naming convention,

<yymmdd>_<file name>_<lastname>.*

where

yymmdd is the year, month, and day in two-digit format (e.g., 150901)
file name describes the file (e.g., assignment1)
lastname is your last name

For example:

150901_assignment1_skinner.docx
150908_assignment2_skinner.do

For assignments, the year, month and day should be the day the assignment is due.

Honor Code

For this course, you are bound by the terms of the Peabody Honor System. Any breach of academic honesty, including cheating, plagiarism, or failing to report a known or suspected violation of the Code will be reported to the Honor Council. In particular, papers must assign credit to the sources you use. Material borrowed from another—quotations, paraphrases, key words, or ideas—must be credited following appropriate citation procedures (footnotes and bibliography). As mentioned above, collaboration is permitted on assignments but is not permitted on your summary paper and codebook. If you have any doubts, please ask me for clarification. Uncertainty about the application of the Honor Code does not excuse a violation.