A method for analyzing raw data collected over a period of time, using a processing/analysis system, to verify an integrity of the raw data collected, the method including: collecting raw data point values over a period of time; using the processing/analysis system: to identify and remove specific ones of said raw data point values determined to be outliers residing outside of a predetermined range of data point values; and for each one of said specific remaining ones of the raw data point values: to examine at least two other ones of the raw data point values obtained at points in time prior to a given one of the raw data point values being examined; to use the at least two other ones of the raw data point values to determine a predicted data point value relative to the given one of the raw data point values being examined; to compare the predicted data point value and the given one of the raw data point values being examined; and from the comparing, determine whether the given one of the raw data point values being examined is a valid data point value; wherein the operation of examining at least two other ones of the raw data point values comprises examining at least two adjacent in time ones of the raw data point values and assigning a weight to each, the weight being greater for the one closest to the given one of the raw data point values, to produce weighted data point values. collecting raw data point values over a period of time; using the processing/analysis system: to identify and remove specific ones of said raw data point values determined to be outliers residing outside of a predetermined range of data point values; and for each one of said specific remaining ones of the raw data point values: to examine at least two other ones of the raw data point values obtained at points in time prior to a given one of the raw data point values being examined; to use the at least two other ones of the raw data point values to determine a predicted data point value relative to the given one of the raw data point values being examined; to compare the predicted data point value and the given one of the raw data point values being examined; and from the comparing, determine whether the given one of the raw data point values being examined is a valid data point value; to identify and remove specific ones of said raw data point values determined to be outliers residing outside of a predetermined range of data point values; and for each one of said specific remaining ones of the raw data point values: to examine at least two other ones of the raw data point values obtained at points in time prior to a given one of the raw data point values being examined; to use the at least two other ones of the raw data point values to determine a predicted data point value relative to the given one of the raw data point values being examined; to compare the predicted data point value and the given one of the raw data point values being examined; and from the comparing, determine whether the given one of the raw data point values being examined is a valid data point value; to examine at least two other ones of the raw data point values obtained at points in time prior to a given one of the raw data point values being examined; to use the at least two other ones of the raw data point values to determine a predicted data point value relative to the given one of the raw data point values being examined; to compare the predicted data point value and the given one of the raw data point values being examined; and from the comparing, determine whether the given one of the raw data point values being examined is a valid data point value; wherein the operation of examining at least two other ones of the raw data point values comprises examining at least two adjacent in time ones of the raw data point values and assigning a weight to each, the weight being greater for the one closest to the given one of the raw data point values, to produce weighted data point values.