Live cell imaging and single particle tracking techniques have become increasingly popular amongst the mathematical biology community. Lysosomes, known for endocytosis, phagocytic destruction, and autophagy, move about the cell along microtubules. Intracellular transport of lysosomes is carried out in membrane-bound vesicles through the use of motor proteins. Single particle tracking methods utilize stochastic models to simulate intracellular transport and give rise to rigorous analysis of the resulting properties, specifically related to transitioning between inactive to active states. We find confidence in our methodology and develop simulations to capture these properties at multiple frames rates. Determining an optimal frame rate for capturing live cell data is necessary in order to successfully infer properties or the underlying mechanisms. Many studies rely on selecting an arbitrary frame rate that satisfies the experimental realms of the work and allows for extraction of specific underlying properties, ranging anywhere from 1Hz to 200Hz. Results show that over the same length of time, data captured at faster frames provides more information than at slower frame rates. We explore this phenomena through a simulation study.