In our department, experimental research is becoming more and more common. Doing experimental research and analyzing data requires some knowledge about methodology and statistics.
For UiL OTS researchers we have a statistical adviser, Kirsten Schutter, to help guide you through the abundant possibilities and resources and advise you on research design, and which methods and statistical analysis to use.
As researcher, you are responsible for your own study. This implies you should be familiar with the methods you are using. You should not expect the statistical adviser to take over the statistical part of your study or to teach you (complicated) methods. Here are some references to get you started.
- A book on experimental methods (in Language acquisition research):
Blom, E., & Unsworth, S. (Eds.). (2010). Experimental methods in language acquisition research. Amsterdam/Philadelphia: John Benjamins Publishing.
- Coursera course on the basics of quantitative research methods:
- Statistics book with SPSS examples in linguistics (you can read it online via UB):
Eddington, D. (2015). Statistics for Linguists: A Step-by-Step Guide for Novices. Cambridge: Cambridge Scholars Publishing.
- A book on experimental methods (in social sciences):
Field, A., & Hole, G. (2002). How to design and report experiments. London: Sage.
- Statistics book with SPSS examples in social sciences:
Field, A.P. (2013). Discovering statistics using IBM SPSS Statistics (4th ed.). London: Sage.
- Statistics book with R examples in social sciences:
Field, A.P., Miles, J. & Field, Z. (2012). Discovering statistics using R. London: Sage.
- Very accessible tutorial for linear models and linear mixed effects models in R:
Winter, B. (2013). Linear Models and Linear Mixed Effects Models in R With Linguistic Applications. arXiv preprint arXiv:1308.5499
- Website with step-by-step tutorials for a lot of basic analyses in SPSS, including a ‘Statistical Test Selector’ – you pay a small fee for 1/3/6 months access:
- Handy website ‘Choosing the correct statistical test in SAS, Strata, SPSS and R’:
- A free online Multilevel modelling course from Bristol University:
This set of modules offers you and introduction into common concepts in statistics, helps you find the correct way to analyse your data and helps you to apply these methods in both SPSS and R. The modules are written by Laura Boeschoten, and are still under development. If you have any remarks, please let the current statistical advisor know. The modules are based on the following literature:
- Gravetter, F. J., & Wallnau, L. B. (2008). Statistics for the behavioral sciences, 6th edition. London: Thomson Wadsworth.
- Peck, R., & Devore, J. (2008). Statistics, The exploration and Analysis of Data, 6th edition. Belmont: Thomson Brooks/Cole.
- Field, A. (2013). Discovering statistics using IBM SPSS Statistics, 4th edition. London: Sage.
- Field, A., Miles, J. & Field, Z. (2012). Discovering statistics using R. London: Sage.
The datasets used in the modules are provided by Andy Field.
Please note that the modules are mainly for reference after a consult with the statistical advisor; as noted in the how-to for planning an experiment. If you’re a research master student, please have your supervisor come along to the meeting.
|0||Step by step guide into performing statistical analysis|
|1||Introduction to Statistics||Data|
|7||Probability and Samples|
|8||Introduction to Hypothesis Testing|
|9||The correlational method||Data|
|10||A Chi Square Test of Independence||Data|
|11||Introduction to the t Statistic|
|12||The t Test for Two Independent Samples||Data|
|13||The paired samples t test||Data|
|14||Introduction to Analysis of Variance|
|15||One Way ANOVA||Data|
|16||Repeated Measures ANOVA||Data|