Retrospective Voting and Quantitative Results Quantitative measurement consists of basic descriptive statistics and crosstabs which relate one variable to another (or other data analysis if appropriate/requested) Analysis of crosstabs incorporate at least one interpretation of the Chi-
Square statistic (see the in-class worksheet to review its calculation. I will provide the Chi-Square critical value for your specific crosstab. If the value you calculate is bigger than the critical value I give you, the result you saw was substantively meaningful and unlikely to have occurred by chance alone.)
Make sure to describe each crosstab in writing. What was the overall pattern you saw? What categories help to illustrate this pattern (e.g.: Around 50% of cat owners reported being Very Happy, compared to around 12% of non-cat owners.)
If you are interested in examining subgroup variation in the pattern (i.e., splitting crosstabs by a 3rd variable as we saw in class), make sure to first present the overall pattern in a crosstab which includes the full sample.
Don’t include quantitative analyses that tell you nothing about your research question! Conclusions (10%)
Conclusions are the most important (and most overlooked) aspect of a research project, so take them seriously. They combine three insights:
A summary of what the findings actually tell you about your research question overall (without reference to specific tests). Give us a general impression of what you found, in a manner that allows no specialists to understand your findings.
A discussion of what your findings add to the literature: did you “fill the gap” you identified in your lit review?
A discussion of what is still needed to more thoroughly answer your research question. This is guidance for future researchers.
