This document discusses various statistical techniques for analyzing metrics and detecting changes, including hypothesis testing, statistical process control (SPC), multivariate adaptive statistical filtering (MASF), and analysis of variance (ANOVA). It provides examples of how each technique works and the assumptions behind them. Specifically, it walks through using MASF and ANOVA to analyze server usage metrics to detect any deviations from normal patterns.

1. Did Something Change? Using Statistical Techniques to Interpret Service and Resource Metrics Frank Bereznay

4. A Note About Bill Mullen

11. Hypothesis Testing – Population Parameters

12. Hypothesis Testing – Population Distribution

13. Hypothesis Testing – Sample Statistics

14. Hypothesis Testing Calculation of the t statistic with 9 (N-1) Degrees of Freedom

15. Hypothesis Testing

20. Statistical Process Control Sample Order Output

21. Statistical Process Control

22. Statistical Process Control Done the correct way: 15 ± .373*4.33

23. Statistical Process Control Without Sub-grouping limit calculation

24. Statistical Process Control Without Sub-grouping limit calculation

51. Midrange Server Example Table of Hourly Usage Metrics Reference Set

57. Midrange Server Example Exception Table for Rest of Week

60. Questions ???