Statistical Analysis of Supplier Standard Deviations PPT

This PPT slide, part of the 120-slide Six Sigma - Sampling Plans & Sample Sizes PowerPoint presentation, presents a statistical framework for evaluating the standard deviations of 2 suppliers, A and B. It outlines the null hypothesis (H0) and the alternate hypothesis (H1), which are fundamental in hypothesis testing. The null hypothesis asserts that the standard deviation of Supplier A is equal to that of Supplier B, while the alternate hypothesis posits that they are not equal. This sets the stage for a comparative analysis of the suppliers' performance metrics.

Key statistical parameters are provided to guide the testing process. The Type I error risk, denoted as ?, is set at 0.05, indicating a 5% chance of incorrectly rejecting the null hypothesis when it is true. This level of significance is standard in many statistical tests, balancing the risk of false positives. The power of the test, represented as 1 - ?, is specified at 0.95, suggesting a high probability of correctly rejecting the null hypothesis when it is indeed false. This is crucial for ensuring that the analysis is robust and reliable.

Additionally, the slide mentions the difference to be detected, represented by ?, with 2 potential ratios provided: ? = sA/sB = 2 or ? = sB/sA = 2. This indicates the specific comparative metrics that will be analyzed, emphasizing the need for a clear understanding of the relationship between the 2 suppliers' standard deviations.

Overall, the slide serves as a concise guide for conducting a statistical analysis aimed at understanding supplier performance, which can be pivotal for decision-making processes in procurement and supply chain management.

This slide is part of the Six Sigma - Sampling Plans & Sample Sizes PowerPoint presentation.

Developed by a Senior Executive and Operational Excellence Coach with experience at organizations including NOKIA, MICROVENTION, and MAGELLAN, this material covers Statistical Sampling Plans and Confidence Interval Analysis using Minitab.

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