The final lecture on quantitative data analysis covered4 specific statistical test:

- Binomial – Given a weighted coin, how many heads will probably result from 30 tosses
- Median – Checks that the medians of two populations are not significantly different
- Mood’s median test – Checks for significant similarity between unrelated samples (non-parametric)
- Kilmogorov-Smirnov – Measure the cumulative difference between data, are the data sets different?
- Friedman – Testing for significant differences across testing intervals on a sample population

The lecture slides included clear examples of these tests. The tutorial followed up with some practical examples using SPSS. After the 4 weeks of quantitative data analysis we now have a decent toolbox specifically for non-parametric data analysis. Our assignment requires application of these tools. I imagine that the assignment will give lease to some of the ambiguities that arise when reasoning from quantitative analysis.