Previous studies have rarely examined the impact of outliers on the decisions about the number of factors to extract in an exploratory factor analysis. The few studies that have investigated this issue have arrived at contradictory conclusions regarding whether outliers inflated or deflated the number of factors extracted. By systematically inducing outliers as well as computer simulations based on real data, the present study demonstrated how outliers affected the decisions about the number of factors to extract using four commonly used and/or recommended decision methods. The studies revealed that both inflation and deflation of the number of factors were found, but the effect depended on (a) the decision methods used and (b) the magnitude and amount of outliers, hence resolving the apparent contradictory conclusions in the previous literature. (Contains 1 note, 6 tables and 3 figures.)