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Minitab Guide: Two-Sample t-Test Parameters PPT


This PPT slide, part of the 120-slide Six Sigma - Sampling Plans & Sample Sizes PowerPoint presentation, presents a structured overview of how to utilize Minitab for conducting a two-sample t-test, focusing on power and sample size calculations. The main section outlines critical inputs required for the analysis, including sample sizes, the difference to be detected, desired power of the test, and estimated standard deviation. Each of these components is essential for ensuring that the statistical test is robust and reliable.

The slide emphasizes the importance of specifying the difference (?) that needs to be detected, which is crucial for determining the sensitivity of the test. The power of the test, indicated as (1 - ?), is highlighted, suggesting that a power of 0.9 is desired. This implies a 90% chance of correctly rejecting the null hypothesis when it is false, which is a significant consideration in hypothesis testing.

Additionally, the standard deviation is mentioned as a necessary input, reflecting the variability within the data. The slide also prompts users to enter the alpha risk, which is the likelihood of making a Type I error. This is a critical factor in hypothesis testing, as it affects the overall validity of the results.

Lastly, the slide includes options for selecting the alternative hypothesis, indicating whether the test is directional (less than or greater than) or non-directional (not equal). This choice impacts the interpretation of the results and should align with the research question being addressed. Overall, this slide serves as a practical guide for users looking to perform statistical analyses using Minitab, ensuring they understand the key parameters involved.



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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