The paper by Felix D. Schönbrodt and Marco Perugini explores the stability of sample correlations in relation to sample size. Using Monte-Carlo simulations, they determine the critical sample size required for a correlation estimate to be considered stable within a specified corridor of stability (COS). The study finds that the required sample size depends on the effect size, the width of the COS, and the desired confidence level. For typical scenarios, a sample size of around 250 is needed for stable estimates. The authors also discuss the impact of non-normal distributions and provide practical guidelines for researchers to ensure accurate and stable correlation estimates.The paper by Felix D. Schönbrodt and Marco Perugini explores the stability of sample correlations in relation to sample size. Using Monte-Carlo simulations, they determine the critical sample size required for a correlation estimate to be considered stable within a specified corridor of stability (COS). The study finds that the required sample size depends on the effect size, the width of the COS, and the desired confidence level. For typical scenarios, a sample size of around 250 is needed for stable estimates. The authors also discuss the impact of non-normal distributions and provide practical guidelines for researchers to ensure accurate and stable correlation estimates.