Laboratories around the world are using the zebrafish model for biomedical research and conducting investigations using morphological, physiological, behavioral, and genomic endpoints. All assays provide information, but physiological and behavioral endpoints or phenotypes are a fast way to understand how an animal is responding to its environment. We investigate the zebrafish model and its relevant assays with particular focus on the photomotor response screening assays. Behavioral time series data is often non-Gaussian distributed and presents a challenge for valid statistical analysis. As such, we have developed both single measure (SM) and repeated measure (RM) nonparametric permutation methods, and compared them to traditional parametric and nonparametric methods. Our proposed methods are sensible for both the zebrafish embryonic photomotor response (EPR) and larval photomotor response (LPR) locomotor screening assays, and they integrate with other zebrafish assays. The SM permutation test does notpreserve the time series aspect of the data, while the RM permutation test does. Both tests provide robust methods for the analysis of in vivo chemical hazard identification in a high throughput research environment.