Tutorial: Research Methods in Political Science (PO3600)
Welcome! This site contains useful material for the tutorials of the module Research Methods for Political Science. In particular, I will use this site to publish links to useful papers, tutorials, or general advice. If you have any questions feel free to get in contact with me. You find the slides of the lectures, homeworks and datasets on Blackboard. This webpage only supplements the information from Blackboard by offering additional material.
Questions about the lectures or tutorials? Please ask them here.
Get and install SPSS
This course is based on SPSS. You are free to use alternative (and free) statistical software such as R or JASP. As a TCD student, you get a free SPSS license from the IT Service. What you need to do: Either you go to the IT Service Desk, get an installation DVD and fill out a form, or you print the form, bring it to the IT Service Desk and download SPSS directly from the TCD download website. Note that you will need to be logged in to the TCD wifi to download the software. Once you got the files, follow the instructions provided in the PDF file.
While we will cover a lot of the SPSS functions in the tutorials, for your homework and research project you will very likely need additional functions.
- SPSS Tutorials: A website with dozens of useful SPSS tutorials.
- Tutorials, Kent State University: An wide range of written and illustrated SPSS tutorials.
- UCLA Tutorials for R, Stata and SAS: Very useful tutorials for the most important statistical analyses.
- Swirl: Learn R in R.
- Moderndive: A great interactive introduction to data visualisation and modelling in R.
- Stackoverflow: Here you will find almost all answers to specific questions.
Information on submitting assignments
Throughout both Michaelmas and Hilary term you will need to submit homeworks, assignments and a research project. You are free to conduct the homework with SPSS or an alternative statistical software (for example Stata or R, but not Excel).
Some general rules:
The assignments must be typed into a LaTeX or Word/Open Office document and submitted as a PDF via Turnitin. Screenshots of the SPSS output are not sufficient as you will need to describe and interpret the results and procedures.
If you include tables, do not use a screenshot, but use the “export” function from SPSS. Please save figures appropriately in high resolution (I recommend PDF as vector graphic formats have the best possible quality).
Add the contents of the SPSS Syntax file/R script/Stata do file at the end of your document. It is good academic practice to present the full code and replication script. While SPSS has a point-and-klick interface, not relying on scripts results in extra work if you need to repeat an analysis. Even more important, only with scripts you can ensure reproducibility of your results. On the topic of reproducibility, have a look at the following links:
To reiterate, please copy the contents from the SPSS syntax file at the end of the submitted document.
Useful links for each tutorial
Below I post a selection of useful links for each tutorial. If you found additional material that might be useful, either open a pull request on GitHub or let me know via email.
Tutorial 1, Hilary Term
- Tutorial Slides (HT 01)
- Overview of t-tests
- One sample t-test
- Two sample independent t-test
- Manifesto Research Project
- Crowd-sourced text analysis
- Tool for quantitative text analysis (comments welcome!)
Tutorial 2, Hilary Term
Tutorial 3, Hilary Term
- Tutorial Slides (HT 03)
- Run a linear regression in SPSS and interpret the output
- Kieran Healy. 2018. Data Visualization: A Practical Introduction
Tutorial 4, Hilary Term
- Tutorial Slides (HT 04)
- How To Visualise Your Data (Financial Times)
- Difference between t-test and F-test
- SPSS Annotated Output Regression Analysis
- Calculating Krippendorff’s alpha
Tutorial 5, Hilary Term
- Tutorial Slides (HT 05)
- SPSS Regression Diagnostics
- Testing Assumptions of Linear Regression in SPSS
- Regression Diagnostics in R
- Reverse Engineering a Regression Table
- Understanding Cook’s Distance Using SPSS
- Influential Observations
Tutorial 6, Hilary Term
- Tutorial Slides (HT 06)
- Recoding Variables in SPSS
- A Protocol for Data Exploration to Avoid Common Statistical Problems
Tutorial 7, Hilary Term
- Tutorial Slides (HT 07)
- Understanding Interaction Effects in Statistics
- Interpreting Interactions in Regression
Tutorial 8, Hilary Term
- Tutorial Slides (HT 08)
- Difference Between Parametric and Nonparametric Tests
- Interpret Odds Ratio in Logistic Regression
Tutorial 9, Hilary Term
- Tutorial Slides (HT 09)
- Predicted Probabilities (in R, but very comprehensible!)
- Calculate predicted probabilities in SPSS
Tutorial 1, Michaelmas Term
- Tutorial Slides (MT 01)
- Introduction to the SPSS Environment:
- Panels, symbols, output viewer
- Syntax editor
- Importing datasets
- Data organisation in spreadsheets
- Calculate mean and standard deviation by hand
- Simulate the distribution of sample means
- Difference between standard deviation and standard error
Tutorial 2, Michaelmas Term
- Tutorial Slides (MT 02)
- Subset data
- Recode variables
- How to name variables and share data
- Change decimals for numeric variables
Tutorial 3, Michaelmas Term
- Tutorial Slides (MT 03)
- Student’s t-test explained
- Calculate t-test by hand
- Calculate t-test in SPSS
Tutorial 4, Michaelmas Term
- Tutorial Slides (MT 04)
- Save and export graphs in SPSS
- Add regression line to plot in SPSS
- Ways to estimate reliability
- Examples of reliability and validity
Tutorial 5, Michaelmas Term
Tutorial 6, Michaelmas Term
- Tutorial Slides (MT 06)
- Merge datasets in SPSS
- Understanding and interpret boxplots
- Cheat sheet for plotting different types of variables
Tutorial 7, Michaelmas Term
- Tutorial Slides (MT 07)
- Interpret results from cross-tables
- Lambda and Gamma
- Calculate Gamma (by hand)
Tutorial 8, Michaelmas Term
- Tutorial Slides (MT 08)
- Calculate correlation coefficient by hand
- Same stats, different graphs
- Choosing the right statistical test
- Choosing a statistical test
- Tutorial: Choosing the correct statistical test