This chapter talks about the analysis of quantitative data, which we have already discussed in the notes Professor Ryan gave us. Although Neuman described the three elements of causality in the third chapter, he elaborates the difference between causality and correlation in this chapter. Based on the third chapter, three things are necessary to establish causality: temporal order, association, and the elimination of plausible alternatives.

In this context, I want to go back to the midterm paper we evaluated one more time. As you all remember, the midterm paper was an experimental study that looked at the relationship between “behavioral intention” to use and “positive mood” while considering uncertainty. The author established temporal order by measuring the mood of the subjects with a survey prior to the judgment task. The tables that are provided (for instance, uncertainty manipulation check with p value less than 0.001) showed that there was an association among the variables. However, I am not sure whether the author did a good job on eliminating alternative explanations for results. As Rosemary indicated, we do not know whether the students consumed the candy or perhaps some students were still a little bit drunk because they went to a club on Thursday night (I used to do this on Thursday nights often during my bachelors degree). Therefore, I believe that in the current format the author shows a correlation between positive mood and behavioral intention to use. However, the elimination of plausible alternatives needs to considered in order to show causality.