1 Sign up for the course
2 Get access to the course materials
The reading materials for the course are distributed through the Zotero reference management system. To get access to the materials:
- Create an user account at Zotero.org
- Email your username to the course instructor
- The course instructor will send you an invitation to a group library, which you need to accept.
After you have accepted the invitation, you can access the material either online with a web browser or by installing the Zotero software on your computer and entering your username and password to the synchronisation options.
3 Start studying for the pre-exam
The pre-exam is organized before the first lecture. More information about the pre-exam is available here.
4 Start working on the first written assignment
Each lecture has a set of readings and a written pre-assignment. These will likely take one or more full work days to complete, so you should start early. See the first lecture assignment here.
Additional resources that will be helpful:
Series of MOOCs that will cover basics of statistics
While the course covers some basics of statistical inference, we focus mostly on how these tools are used in management research. It may therefore be helpful to review some of the basics of statistics before the class. The best way to do this is to watch some of the lectures in the "Data analysis and statistical inference" online course on Coursera:
The following courses are relevant:
- Introduction to Probability and Data
- Inferential Statistics
- Linear Regression and Modeling
Getting familiar with a statistical software
Because we have limited time to work with computers in the class, it is highly recommended that you familiarise yourself with the statistical software that you plan to use before the start of the first class.
Check out the getting started manual and work through the sample session (Chapter 1)
- Getting Started with Stata for Windows
- Getting Started with Stata for Mac
- Getting Started with Stata for Unix
Stata also has a Youtube channel with tutorial videos. The following video is a good starting point:
For more, see http://www.stata.com/links/video-tutorials/
R and RStudio
If you plan to use R for the data-analysis exercises, it is recommended that you do an online tutorial before starting the class. R has a learning curve, and without learning the basics before the course, we will end up spending too much time in learning R instead of learning how to use R for data analysis.
DataCamp provides good, free online tutorials
Particularly, this course is likely to be useful
The MOOCs listed above also use R and provide tutorial on its use.
You should also probably take a look at these books:
Kabacoff, R. (2011). R in action data analysis and graphics with R. Shelter Island, NY; London: Manning ; Pearson Education [distributor].
Wickham, H., & Grolemund, G. (2016). R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. O’Reilly Media, Inc.
Wickham's book presents a more modern take on R. The book is available here http://r4ds.had.co.nz
While it is possible to complete the course using SPSS, this is not a good idea because SPSS is not a good choice for serious data analysis. However, if you just want to do the first assignment, which is mandatory for passing the course, that is doable with SPSS.
For Finnish students
Mikko Ketokivi's book is an excellent resource for basics of quantitative research:
Ketokivi, M. (2015). Tilastollinen päättely ja tieteellinen argumentointi (2nd ed.). Helsinki: Gaudeamus.