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Confidence Limits, Power, and Sample Size Estimation in Statistical Analysis

This discussion outlines the concepts of confidence limits, power, and sample size estimation in statistical analysis. It covers topics such as one-sample and two-sample scenarios, population variance known or unknown, and how to read data in SAS.

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Confidence Limits, Power, and Sample Size Estimation in Statistical Analysis

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Presentation Transcript

  1. Discussion 2 1/13/2014

  2. Outline • Confidence limits • Power • One sample • Population variance known or unknown • Two sample • Population variance known or unknown • Sample size estimation • One sample (confidence interval) • Two sample (detect differences between two means) • How to read data in SAS

  3. Questions?

  4. Confidence Limits • If we take repeated samples of size n and construct confidence intervals we can expect (1 – α) x 100% of the intervals to contain the true population mean Example: n = 14, α = 0.05, and standard error of mean = 0.3279

  5. Power • One sample – detect a difference between a mean and value previously known If you know population standard error If you don’t know population standard error

  6. Power • Two sample – detect a difference between two means If sample size is different between group1 and group 2 If sample size is the same between group 1 and group 2 If the population variance is given to you, substitute it into the equation instead of the sample pooled variance

  7. Sample Size Estimation • One sample – sample size to estimate a confidence interval of a mean Where Remember to do iterations when estimating sample size

  8. Sample Size Estimation • Two sample – Sample size to detect differences between two means with a give α and power Where Remember to do iterations when estimating sample size

  9. How to read data in SAS • Looked at correct and incorrect methods to read data in SAS using the data from Lab 1 Example 4

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