Based on a stochastic extension of Karamata’s theory of slowly varying functions, necessary and sufficient conditions are
established for weak laws of large numbers for arbitrary linear combinations of independent and identically distributed nonnegative
random variables. The class of applicable distributions, herein described, extends beyond that for sample means, but even
for sample means our theory offers new results concerning the characterization of explicit norming sequences. The general
form of the latter characterization for linear combinations also yields a surprising new result in the theory of slow variation.