Hundreds of studies examine gender differences in performance. Rather than conduct an additional study, one can synthesize the existing studies to find an overall outcome.
Meta-analysis refers simply to the application of quantitative or statistical methods to combine evidence from numerous studies. Meta-analysis can tell us, when we aggregate over all the available studies, whether there really is a gender difference in mathematical ability. It can tell us the direction of the difference: do males score higher on average or do females? And it can also tell us the magnitude of any gender difference.
The d statistic, or effect size, is used to measure the gender difference. To obtain d, the mean score of females is subtracted from the mean score of males in a particular study, and the result is divided by the pooled within-gender standard deviation. Essentially, d tells us how far apart the means for males and females are in standardized units. d can have positive or negative values. A positive value means that males score higher, and a negative value means that females score higher. To give a tangible example, the gender difference in throwing distance is + 1.98.
In a meta-analysis, d is computed for each study, and then ds are averaged across all studies. Because meta-analysis aggregates over numerous studies, a meta-analysis typically represents the testing of tens of thousands, sometimes even millions of participants. Thus, the results should be far more reliable than those from any individual study.
How do we know when a d, an effect size, is small or large? The statistician Jacob Cohen provided the guideline that a d of 0.20 is small, 0.50 is moderate, and 0.80 is large.
their performance on standardized mathematics tests, because students experience mathematical problem-solving in physics and chemistry classes.
Concerning gender differences in verbal ability, meta-analysis of 165 studies representing the testing of 1.4 million persons showed superior performance by females but the difference is very small (d = −0.11).3 The question of gender differences in spatial ability, a relevant skill in many fields of science and engineering, is complicated because there are many types of spatial ability and many tests to measure them. With regard to gender differences in three dimensional