-Following statistical metrics are proposed as performance trend
-indicators over the rolling window of last <N> sets of historical
-measurement data:
-
- - Q1, Q2, Q3 : Quartiles, three points dividing a ranked data set
- into four equal parts, Q2 is the median of the data.
- - IQR = Q3 - Q1 : Inter Quartile Range, measure of variability, used
- here to calculate and eliminate outliers.
- - Outliers : extreme values that are at least (1.5 * IQR) below Q1.
-
- - Note: extreme values that are at least (1.5 * IQR) above Q3 are not
- considered outliers, and are likely to be classified as
- progressions.
-
- - TMA: Trimmed Moving Average, average across the data set of the
- rolling window of <N> values without the outliers. Used here to
- calculate TMSD.
- - TMSD: Trimmed Moving Standard Deviation, standard deviation over the
- data set of the rolling window of <N> values without the outliers,
- requires calculating TMA. Used for anomaly detection.
- - TMM: Trimmed Moving Median, median across the data set of the rolling
- window of <N> values with all data points, excluding the outliers.
- Used as a trending value and as a reference for anomaly detection.
+Following statistical metrics are used as performance trend indicators
+over the rolling window of last <N> sets of historical measurement data:
+
+- Q1, Q2, Q3 : Quartiles, three points dividing a ranked data set
+ of <N> values into four equal parts, Q2 is the median of the data.
+- IQR = Q3 - Q1 : Inter Quartile Range, measure of variability, used
+ here to calculate and eliminate outliers.
+- Outliers : extreme values that are at least (1.5 * IQR) below Q1.
+
+ - Note: extreme values that are at least (1.5 * IQR) above Q3 are not
+ considered outliers, and are likely to be classified as
+ progressions.
+
+- TMA : Trimmed Moving Average, average across the data set of <N>
+ values without the outliers. Used here to calculate TMSD.
+- TMSD : Trimmed Moving Standard Deviation, standard deviation over the
+ data set of <N> values without the outliers,
+ requires calculating TMA. Used for anomaly detection.
+- TMM : Trimmed Moving Median, median across the data set of <N> values
+ excluding the outliers. Used as a trending value and as a reference
+ for anomaly detection.