Hello!
Here you will find the tutorial slides and some additional materials on topics covered on 2020 HT PO3110, Research Methods for Political Science B's tutorials.
The core module material, such as lecture slides, homeworks and datasets can be found on Blackboard.
It is always better to address doubts you may have during our tutorials, as it may help some of your classmates as well. In any case, I am available to meet upon request, preferrably on Tuesdays (12 to 13). You can reach me through my email: [email protected]
The statistical sofware used in this course is SPSS. 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 network (cabled) to download the software. Once you got the files, follow the instructions provided in the PDF file.
- The licence code is on the tcd software website, HERE.
- If you scroll down on the licence page there should be an heading for the 2018/19 licence.
- You are free to use alternative (and free) statistical software such as R or JASP.
Andrea Salvi has kindly organized a collection of useful links to help you develop software and statistical skills in addition to the work we will be doing in our tutorials:
- 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: Simulates an R workspace allowing you to 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.
Throughout this 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:
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The assignments must be typed into a LaTeX or Word/Open Office document and submitted as a PDF via Turnitin (see the Syllabus for more details). Screenshots of the SPSS output are not sufficient as you will need to describe and interpret the results and procedures.
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If you include tables, do not use a screenshot, but use the "export" function from SPSS. Please save figures appropriately in high resolution (We recommend PDF as vector graphic formats have the best possible quality).
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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:
- AJPS guidelines for preparing replication files
- Reproducible research using the SPSS syntax option
- SPSS online video tutorials
To reiterate, please copy the contents from the SPSS syntax file at the end of the submitted document.
Below I post the links to the slides I use in our tutorials and a selection of useful links for each tutorial as organized by the previous PO3110 TA Andrea Salvi. You can go to Andrea's github page to access the material from Michaelmas Term 2019 and more useful links related to topics covered in his tutorials.
- 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 (by Stefan Mueller)
- Run a linear regression in SPSS and interpret the output
- Kieran Healy. 2018. Data Visualization: A Practical Introduction
- Simulate the coverage of confidence intervals
- How To Visualise Your Data (Financial Times)
- Difference between t-test and F-test
- 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
See Tutorial 4!
- Pseudo R Squares
- Regression with Categorical Predictors
- Creating Dummy Variables in SPSS
- Interpretation of Dummy Variables (intuitive examples)
This repo has been forked from 2019 PO3110 repo and will be further updated in the course of the 2020 HT. We thank both Andrea Salvi and Stefan Mueller, the TA before him, for the amazing resources.