1. A system for adjusting a set of predicted future data points for a time series data set, comprising: a processor and; a non-transitory computer readable storage medium containing instructions that, when executed with the processor, cause the processor to perform operations including: receiving the time series data set, wherein the time series data set includes a plurality of data points that correspond to a plurality of discrete values; generating a set of counts for the time series data set by analyzing the time series data, wherein a count corresponds to a number of instances of a particular discrete value in the time series data set; automatically selecting an optimal discrete probability distribution for the set of counts from a set of candidate discrete probability distributions based on a selection criterion; generating a set of parameters corresponding to the optimal discrete probability distribution; selecting a statistical model for the time series data set, wherein selecting the statistical model includes using a set of statistical models and the selection criterion; generating the set of predicted future data points for the time series data set, wherein generating the set of predicted future data points includes using the selected statistical model; adjusting the set of predicted future data points for the time series data set, wherein adjusting the set of predicted future data points includes using the set of parameters corresponding to the optimal discrete probability distribution; and using the adjusted set of predicted future data points to provide a predicted future data point based on received user input associated with the time series data set.