Unsure of how to compare non-paired values

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In summary, the speaker is trying to determine if two numbers are significantly different, but is unsure of how to do the statistics. They have four arrays of numbers and can use a student's t-test to determine the difference between two arrays. They have also performed a mathematical calculation on each value in the arrays to generate four new arrays. Now, they want to compare the difference between two of the new arrays to the difference between the other two. However, they are unsure how to do this as they cannot simply take the difference in a pairwise manner. They have also tried using propagation of uncertainty but are unsure if this is the best method. The speaker is asking for help in determining if the values are significantly different.
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Richter915
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I am currently trying to show that two numbers are significantly different but I am unsure of how to do the statistics. I'll provide a brief description below.

I have 4 arrays: Array A Array B Array C and Array D
I can determine the difference between 2 arrays using a student's t-test
From each value within each array, I performed a simple mathematical calculation - let's just say I took the natural logarithm of each value.
I now have four new arrays which is from the calculations done on each value, Array A' Array B' Array C' and Array D'
Again, I can do a pairwise analysis of pairs of arrays using a student's t-test to determine significance.
What I want to do now is take the difference between two arrays (A' and B') and compare that to the difference between the other two arrays (C' and D'). Now, I can't simply take the difference in a pairwise manner (as in, value one of A' minus value one of B') so I have to take a difference of means.
So now I've generated the difference of these two means but I do not know how to do the variance of this value or to determine if these difference of means values are actually different from one another.

I've tried using propagation of uncertainty in order to determine uncertainty of these values but I am unsure if this is the best way. Either way, I am unsure if these values are significantly different.

Any help on this would be appreciated. Thanks.
 
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You haven't explained your problem clearly. I suggest you try again.

For example, you say you are trying to find if two numbers are significantly different, but you mention 4 arrays of numbers. Also, you say you transform the numbers in the arrays and get new arrays, but you say you "can't simply take the difference in a pairwise manner (as in, value one of A' minus value one of B' " and it isn't clear whether you mean that this operation is impossible or whether it is possible, but, for some reason, not meaningful.
 

FAQ: Unsure of how to compare non-paired values

1. What is the difference between paired and non-paired values?

Paired values refer to a set of data where each individual data point has a specific connection or relation to another data point. Non-paired values, on the other hand, do not have any specific connections or relations between data points.

2. How do I compare non-paired values?

To compare non-paired values, you can use statistical tests such as the t-test, ANOVA, or non-parametric tests like the Wilcoxon rank sum test. These tests take into account the variation and distribution of the data to determine if there is a significant difference between the groups.

3. Can I use a paired t-test to compare non-paired values?

No, a paired t-test is specifically designed for paired data, where there is a specific connection between each data point. Using a paired t-test on non-paired data would not give accurate results.

4. Is there a preferred method for comparing non-paired values?

The preferred method for comparing non-paired values may depend on the specific data and research question. It is important to carefully consider the characteristics of the data and consult with a statistician to determine the most appropriate method.

5. What are some potential limitations of comparing non-paired values?

One limitation of comparing non-paired values is that it does not take into account potential confounding variables that may affect the relationship between the variables being compared. Additionally, certain statistical tests may have assumptions that need to be met for accurate results, and these may not be applicable to all types of non-paired data.

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