Calculating P-value comparing two percentages of accuracy?

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SUMMARY

This discussion focuses on calculating the p-value for comparing the accuracy of two microbial identification methods, where Method 1 achieved 90% accuracy and Method 2 achieved 60% accuracy. The user inquired about the appropriate statistical method to apply, indicating confusion regarding the use of chi-squared tests and the distinction between paired and un-paired observations. It was suggested that the user should consider the "t-test for equality of means" for un-paired observations, depending on the sample application context.

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  • Understanding of p-value and its significance in hypothesis testing
  • Familiarity with chi-squared tests for categorical data
  • Knowledge of t-tests, specifically the "t-test for equality of means"
  • Basic concepts of paired vs. un-paired observations in statistics
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  • Research the application of chi-squared tests for comparing proportions
  • Learn about the "t-test for equality of means" and its assumptions
  • Explore methods for calculating p-values in clinical research contexts
  • Study the differences between paired and un-paired statistical tests
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Clinical researchers, biostatisticians, and anyone involved in comparing the effectiveness of different methods in microbial identification or similar fields.

phys-lexic
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I have been out of unversity statistics and biometry for a few years do date. I am working in a clical research facility and we are comparing two methods of microbial identification and am now working on the results / charts / statistics. Forgive me for my ignorance, but I am forgetting which method would I use to calculate the p-value for comparing percentages; i.e. out of 100 samples method 1 was 90% accurate and method 2 was 60% accurate (random values). I was going through my old notes and tried to apply chi-squared, etc. It seems I didn't retain much.

Thanks in advance.
 
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You haven't described a specific situation. For example, were both methods applied to each of 100 samples? Or was one method applied to 100 samples and the other method applied to 100 different samples?

Perhaps your old notes deal with "paired" and "un-paired" observations. Is the accuracy of an application of a method to a single sample a result like 0.93? For un-paired observations, look up the "t-test for equality of means".
 

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