By analyzing seven-day travel logs from Los Angeles during 20112013, we contribute to the understanding of intrapersonal day-to-day travel variability (IDTV) in relation to socio-demographic and land-use characteristics and the implication of travel survey duration for travel parameter estimates. Our main sample included 2,395 person-days from 352 individual participants in 219 households. Our analytical methods included linear regressions and random sampling experiments. Our Feasible Generalized Least Squares (FGLS) regression models revealed that many factors significantly influenced IDTV, such as gender, age, income, and household type. However, the observed socio-demographic and land-use characteristics could only explain a small portion of IDTV. The random sampling experiments enabled us to contrast travel variables measured from the seven-day master sample with those from subsamples of a shorter period (one to six days). The optimal duration for a travel survey may depend on the specific travel variables measured, and we provide evidence that studies of transit and non-motorized travel will require longer surveys than studies of car travel. In conclusion, the conventional one-day approach is likely to produce imprecise parameter estimates due to the intrapersonal day-to-day travel variability. We recommend that transportation professionals and policy makers consider shifting from the conventional one-day approach toward a multi-day approach. Surveys that focus on the modes of walking, biking, and transit should consider data collection for at least seven days.