1. A computer-implemented method for identifying events of interest in web analytics data, comprising: at a computer server having one or more processors and memory for storing programs to be executed by the one or more processors: storing web analytics data for a web page in a device, wherein the web analytics data comprises a plurality of prior time-value pairs, each time-value pair including a value of one of a plurality of attributes associated with the web page and a time associated with the value; collecting a new time-value pair for the particular attribute, the new time-value pair including a new value associated with the web page and a new time when the value was determined; estimating a predicted value for the attribute and associated error-variance at the new time for the predicted value by applying a forecasting model to the plurality of prior time-value pairs in respective subsets of the web analytics data; and tagging the collected new time-value pair if the value of the new time-value pair is outside the error variance of the predicted value of the forecasting model for the particular attribute; adding to the collected web analytics data for the web page the new time-value pair including a tag indicating whether the new value is an anomaly and a significance factor if the new value is an anomaly, wherein the significance factor is associated with the error variance of the predicted value of the forecasting model; for the new time-value pair and the particular attribute, determining the significance factor such that, when the error-variance is multiplied by the significance factor, the value of the time-value pair is inside the factored error-variance of the predicted value; and in response to a request from a client application for analytics information, the request including a significance threshold for one or more of the attributes, reporting to the client application the new time-value pair if the significance factor for the time-value pair exceeds the significance threshold.