Effects and the size of effects are proposed as a key way to overcome the limitations of significance testing in modern statistics. However, traditionally, effects are usually added on to the statistical testing procedure. This chapter proposes instead thinking first about what effects to look for in the context of the research and its maturity within the discipline of HCI. The main types of effect, changes in location, stochastic dominance and (co)variation, are described. Consideration of which of these effects that current best knowledge can predict leads to choosing the test most suitable to find those effects.