  A day in the life of a person involves a broad range of activities which are
common across many people. Going beyond diurnal cycles, a central question is:
to what extent do individuals act according to patterns shared across an entire
population? Here we investigate the interplay between different activity types,
namely communication, motion, and physical proximity by analyzing data
collected from smartphones distributed among 638 individuals. We explore two
central questions: Which underlying principles govern the formation of the
activity patterns? Are the patterns specific to each individual or shared
across the entire population? We find that statistics of the entire population
allows us to successfully predict 71\% of the activity and 85\% of the
inactivity involved in communication, mobility, and physical proximity.
Surprisingly, individual level statistics only result in marginally better
predictions, indicating that a majority of activity patterns are shared across
{our sample population}. Finally, we predict short-term activity patterns using
a generalized linear model, which suggests that a simple linear description
might be sufficient to explain a wide range of actions, whether they be of
social or of physical character.
