Smooth pursuit eye movements are variable, even when the same tracking target motion is repeated many times. We ask whether variation in pursuit could arise from noise in the response of visual motion neurons in area MT. In physiological experiments, we evaluated the mean, variance, and trial-by-trial correlation in the spike counts of pairs of simultaneously recorded MT neurons. The correlations between responses of pairs of MT neurons are highly significant and are stronger when the two neurons in a pair have similar preferred speeds, directions, or receptive field locations. Spike count correlation persists when the same exact stimulus form is presented repeatedly. Spike count correlations increase as the analysis window increases because of correlations in the responses of individual neurons across time. Spike count correlations are highest at speeds below the preferred speeds of the neuron pair, and increase as the contrast of a square wave grating is decreased. In computational analyses, we evaluated whether the correlations and variation across the population response in MT could drive the observed behavioral variation in pursuit direction and speed. We created model population responses that mimicked the mean and variance of MT neural responses as well as the observed structure and amplitude of noise correlations between pairs of neurons. A vector averaging decoding computation revealed that the observed variation in pursuit could arise from the MT population response, without postulating other sources of motor variation.