POL S 501: Advanced Research Design & Analysis (Grad Stats I)
Tuesday 1:30 pm - 4:20 pm, Smith Hall 220 lab
Professor: Matt A. Barreto
Teaching Assistant: Loren Collingwood
This is the second course in a graduate sequence on research design and data analysis. Building on the foundations in POLS 500, this course will teach you how to test your hypotheses in a rigorous and appropriate scientific manner. Even if empirical data analysis and statistics are not at the forefront of your research agenda, they play a very important role in social science research, books and articles today so it is very important that everyone of us has a basic understanding of data analysis and regression models so we can read, write, understand, and critique the existing literature and scholarship in our subfield.
This course will be taught primarily using the statistical software package Stata, and as such, we will spend considerable time learning how to use Stata, and how to manage our various datasets. Knowing the math and statistics behind the analysis is essential, and you will learn this in is class, however if you can not put it to practice correctly in a statistical package, that knowledge is not very useful. Thus, you will learn not only the statistics behind the curtain, but also learn, in-depth, how to create, use, manage, and analyze the data. Throughout the quarter, we will also replicate all our work in a second statistical software package, R, so you can learn the basics of R which will be used in the following sequence, POLS 503, and POLS 510. You should plan to have both of these programs installed on your own personal machine, and you should also sign up for a CSDE login, so you can remote access to Stata and R and other software.
Finally, we will spend a considerable amount of time learning and practicing how to present your data analysis findings. If you can not present your research findings in a coherent and compelling way to your audience/reader, it doesnt matter how sophisticated your methods are. One of the most important things you can master as a scholar is being able to give a high quality presentation of research findings, including bullet points, data tables, charts and graphs.
Books / Articles:
There are four books we will be using in this class for different degrees and purposes. All four are important starting points in learning how to apply statistical analysis to political science research questions, and also how to implement and manage your data in Stata. Other readings may be found online, or academic journals, as necessary, and I will notify you of those, if and when we use additional materials.
Research outline (1 page) Cr/NC Extended outline (5 pages) Cr/NC Lab Section 20 points Homeworks 20 points Research presentation 30 points Final Stats Paper (20 pages +/-) 30 points -------------------------------------------------------------------------------- TOTAL 100 pointsTentative Course Outline: (subject to change)
Week 1: Weds: Welcome and Introductions Fri: Getting Started With Stata, Ch 1-2 / Hamilton Ch 2 Week 2: Weds: W&W Chapters 1 2 Descriptive Statistics and Probability Fri: Getting Started With Stata, Ch 3-5, Ch 13 Week 3: Weds: W&W Chapters 3 5 Distributions of Variables Fri: Hamilton Ch 4; Mitchell Ch 5 Week 4: Weds: W&W Chapter 6 8 Samples and Point Estimates Week 5: Weds: W&W Chapter 9 & 17 Hypothesis Testing, Chi-Squre Fri: Hamilton Ch 5; Mitchell Ch 6 MUST HAVE YOUR DATASET PICKED OUT TO SHARE IN LAB Week 6: Weds: W&W Chapters 15, then 11 12 Correlation and Intro to Regression Fri: Hamilton Ch 6 Week 7: Weds: W&W Chapters 13 14 Regression Part II Fri: Hamilton Ch 7 Week 8: Weds: Data management tips and tricks in Stata Fri: Mitchell Ch 3-4 Week 9: Weds: Using Interaction terms, and post-estimation techniques Fri: Mitchell Ch 4, 5, 9 Week 10: Weds: Final Presentations in class (PowerPoint) Fri: Final Presentations in class (PowerPoint) Finals: Mon or Tues: Poster Presentations to Department (Gowen 1A)