Meta-analysis is the process of quantitatively synthesizing results from numerous experimental studies. One of the main goals for conducting a meta-analysis is to estimate an overall or combined effect of an intervention/s across multiple studies. For example, John Hattie’s Visible Learning (2009) conducted a synthesis of meta-analyses of research from a variety of educational contexts measuring a large number of educational interventions, so to quantify the effect that each contributor had on the outcome of student learning and achievement. The broader the pool of research data that is included, the more accurate the quantitative estimate can be on how much particular contributor’s (e.g., teacher feedback) affect student achievement learning and achievement over others (e.g., homework).
Using effect sizes is one of the most common ways of robustly assessing the effects of interventions across studies. Further, effect sizes themselves promote scientific inquiry because when a particular experimental study has been replicated, the different effect size estimates from those studies can be easily combined to produce an overall best estimate of the size of the intervention effect.
The bases of the method are straight forward and much of the usefulness of meta-analysis is its simplicity. This site provides an excellent description of meta-analysis.