Question

In general, what does an “effect size” refer to, and how is it relevant to the study of gender differences/similarities? How do common assumptions about gender differences match (or not match) the actual effect sizes of the studies? Understand what different numerical effect sizes tell us.

What are a meta-analysis and meta-synthesis, and how are they helpful in understanding gender differences?

Gender differences, and possible explanations for the differences, in each of the following: aggression, emotionality, verbal communication

What is the variability hypothesis, and how was it historically used to discriminate?

What are some problems that can be caused by “over-assuming” gender differences?

Understand the results of the 2007 EAR study.

Understand some strengths and limitations of ways we can examine gender/sex differences through research.

Answer 1

Effect size helps in understanding if there are differences between two groups in a study and further quantifying the extent of this difference. One way of visualising an effect size is to check how much the distribution of scores of the two groups overlap with one another. In gender studies, there is considerable debate whether or not differences between men and women lead to different results in a study. In particular, researchers are interested in understanding whther a particular study would favour a certain gender over the other. In that case, the findings derived from such a study are subject to scrutiny and revision. Computing the effect size would provide a knowledge of whether or not that is the case, and if so, how large or small the differences are thereby allowing the research to draw generalisable conclusions.

Please post the other questions separately.