| Measure | Use |
|---|
| Effect size | Indicates how much one variable affects another. Effect size ranges from 0 to 1: An effect size of 0.2 is called small, 0.5 moderate, and 0.8 large. |
| Significance | Indicates whether the results might have occurred by chance. A finding that chance would produce the results only 5 times in 100 is significant at the 0.05 level. A finding that chance would produce the results once in 100 times is significant at 0.01; once in 1000 times is significant at 0.001. |
| Cost benefit analysis | Calculates how much a particular independent variable costs versus how much it saves. This is particularly useful for analyzing public spending. For instance, one cost-benefit analysis showed that every dollar that the Ontario provincial government has invested in full-day kindergarten yields $2.42 in benefits (The Centre for Spatial Economics, 2010). |
| Odds ratio | Indicates how a particular variable compares to a standard, set at 1. For example, one study found that the odds ratio of Canadian university students finding employment related to their field of study is 5.267 for those in health sciences, 2.018 for those in education, and 1.951 for those in mathematics/computer/information sciences (Boudarbat & Chernoff, 2009). |
| Factor analysis | Hundreds of variables could affect any given behaviour. In addition, many variables (such as family income and parental education) may overlap. To take this into account, analysis reveals variables that can be clustered together to form a factor, which is a composite of many variables. For example, SES might become one factor, child personality another. |
| Meta-analysis | A “study of studies.” Researchers use statistical tools to synthesize the results of previous, separate studies. Then they analyze the accumulated results, using criteria that weight each study fairly. This approach improves data analysis by combining the results of studies that were too small, or too narrow, to lead to solid conclusions. |
| Sources: Alasuutari et al., 2008; Duncan & Magnuson, 2007; Hubbard & Lindsay, 2008. |