Testing hypothesis statistics ppt, prek-12 report
This is especially relevant with time series data where the data are sequenced by time. In this section we present a simple test to determine whether there is autocorrelation aka serial correlationi.
In fact, if we highlight the range I3: In the example above, an overall defect rate of 2. The best controls are those that require no monitoring irreversible product or testing hypothesis statistics ppt design changes.
J6 of Figure 1. For each value of alpha.
A value substantially below 2 and especially a value less than 1 means that the data is positively autocorrelated, i. In our outdoor furniture manufacturing example, the team must understand the reasons behind two of the biggest Pareto items discovered in the Measure phase: Step 4 — Improve The Improve phase focuses on fully understanding the top causes identified in the Analyze phase, with the intent of either controlling or eliminating those causes.
Since most regression problems involving time series data show a positive autocorrelation, we usually test the null hypothesis H0: A value of d substantially above 2 means that the data is negatively autocorrelated, i.
But oftentimes there are process settings, procedures, etc. In cases like this the Six Sigma team should do everything possible describing essay home error-proof the process, and should then add the appropriate checks and balances to the quality system for the long run.
J6 and enter either of these formulas and then press Ctrl-Shft-Enter the result will be the same as shown in range I3: In most cases there will be no more than three causes that must be controlled in order to achieve success — if too many causes are identified, then the team has either not isolated the primary causes or the project goal is too ambitious to achieve success with a single project.
The Durbin-Watson test uses the following statistic: The Analyze phase deploys a number of tools for collecting team input and conducting objective experiments to identify or confirm top causes. A Six Sigma process has a sigma level of six, and for all practical purposes is considered a defect-free process over the long role enzymes photosynthesis, provided that adequate controls are in place to maintain capability.
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