Researchers find valuable to make observations over time. Repeated measures allow gaining insights on the phenomena under study and maximizing the use of the experiment. Measurements made multiple times on the same experimental unit or subject are expected resemble and to be correlated to each other. As result, the statistical analysis repeated measures requires special considerations. The objective of this presentation is to introduce basic concepts to carry out the statistical analysis and interpretation of datasets with repeated measures. As an example, canopy temperature measured on corn inbred lines will be presented. Under drought conditions canopy temperature vary according to the soil water status and irrigation management. Learning about canopy temperature responses over time can help to understand inbred line responses to drought conditions. The corresponding data analysis software and outputs will be presented to be used as guide.