  # Test of Association

When you hear the term Test of Association in statistics, it usually means the Chi-Square Test. However, it’s used in an informal sense to mean many things. Loosely speaking, any time you’re trying to find out if two variables are linked in some way, you’re testing for association. Depending on the context, you could be using a diagram (like a scatter plot) to show an association between variables or using a hypothesis test to demonstrate statistically that relationships exist between variables.

A bivariate association test involves one independent variable and one dependent variable. Multivariate association tests involve more than two variables.

## Test Vs. Measure of Association

Typically, a Measure of Association quantifies the relationship between two groups. A Test takes this a step further and assigns statistical significance to your results. What can get a little confusing is that some authors will lump all tests and measures in the same theoretical basket (calling them all “tests”). There is a subtle difference between the two (a test is a bit more rigorous than a measure), but for practical purposes you probably won’t be aware of a difference.

## Common Measures of Association

The relative risk or odds ratio can show how strong the association is between risk factors and traits. These are not hypothesis tests though, so you won’t know if your results are statistically significant.

## References

Gonzalez-Chica, D. et al. (2015). Test of association: which one is the most appropriate for my study? An Bras Dermatol.Jul-Aug; 90(4): 523–528.
Statistical Tests of Assotiation. Retriveed MArch 2, 2019 from: http://hihg.med.miami.edu/code/http/modules/education/Design/CoursePageContent.asp?ID=188

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Statistical concepts explained visually - Includes many concepts such as sample size, hypothesis tests, or logistic regression, explained by Stephanie Glen, founder of StatisticsHowTo.