Mobile phones are gaining in popularity as a data collection instrument in many fields of research, given their ability to reduce study costs, data entry errors, and study participant burden relative to traditional methods of data collection. Moreover, mobile phones introduce new types of data that can be collected, such as GPS location traces. Despite opportunities, researchers and statisticians face challenges in learning about the array of emerging mobile technologies that are at their disposal and how best to utilize mobile phones in their studies. In this vein, this webinar will provide a brief introduction to mobile phone-based data collection and analysis, with an emphasis on applications in public health studies. The first part of the webinar will focus on study design considerations, including data security protocols, the level of assessment sophistication that is needed (e.g., smart phone app versus SMS text), types of data that can be collected, and trade-offs in different data types. The second part of the webinar will discuss analytic approaches for mobile phone data that often consists of data collected over many time points. Discussion will include the analysis of episodic patterns, such as drug use, and extensions of traditional longitudinal regressions to model mean responses and variation over time. Analyses will be applied to mobile data on substance use in adolescents and data on diet and exercise in mothers. Code to implement analyses in SAS and R is available.