How to compare these two sets of data?

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Discussion Overview

The discussion revolves around comparing two sets of experimental data, specifically how to mathematically assess the differences between the results obtained from two instruments measuring the same dependent variable (Y) against a concentration (X). The focus is on identifying the extent of error and the reliability of the measurements based on the available data.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant seeks methods to quantify the error between two experimental data sets, noting that the experiments were similar but yielded slightly different results.
  • Another participant mentions that the choice of statistical tests depends on the nature of the data provided.
  • Concerns are raised about the lack of repetition tests for the same instrument at the same concentration, which complicates the assessment of measurement accuracy.
  • It is noted that the differences between instruments are smaller than the differences in concentrations, suggesting that the instruments may not be systematically different.
  • A suggestion is made to calculate the differences between measurements at each concentration and find the standard deviation of these differences, assuming no systematic differences exist.
  • Clarification is sought on what additional data would be necessary to provide a more thorough analysis.
  • More repetitions of measurements are suggested as a way to improve the reliability of the analysis.

Areas of Agreement / Disagreement

Participants express uncertainty regarding the systematic differences between the two sets of measurements and the adequacy of the data for drawing specific conclusions. There is no consensus on the best approach to analyze the data due to the varying conditions and assumptions involved.

Contextual Notes

The discussion highlights limitations in the data, such as the absence of repeated measurements and the potential impact of experimental setup details on the results. These factors contribute to the uncertainty in determining measurement accuracy.

Chemist125
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Hi

I have two sets of data, y as a function of x, for two different experiments.

Y is the dependent variable, an instrument reading, x is the dependent variable, a concentration of something in a solution.

Plotting the data in excel gives me 2 curves.

The experiments were essiantially the same, but the results are slightly different, I want to compare how much 'error' there is by comparing how close the data/curves from each experiment lie to each other. Is there some way I can do this mathematically?


Chem125
 
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There are multiple tests, which test is appropriate here depends on the data.
 
mfb said:
There are multiple tests, which test is appropriate here depends on the data.

I attached an excel sheet with example data.

What do you think?

Thanks
 

Attachments

Chemist125 said:
I attached an excel sheet with example data.

What do you think?

Thanks
- the differences between the instruments are way smaller than the differences between the concentrations
- there is no repetition test where the same instrument was tested with the same concentration multiple times, therefore it is impossible to determine the accurary of the measurements based on that data alone. That would be really interesting.
- there is no clear systematic difference between the two instruments

The data is not sufficient to draw more specific conclusions, independent of the analysis method.
 
mfb said:
- the differences between the instruments are way smaller than the differences between the concentrations
- there is no repetition test where the same instrument was tested with the same concentration multiple times, therefore it is impossible to determine the accurary of the measurements based on that data alone. That would be really interesting.
- there is no clear systematic difference between the two instruments

The data is not sufficient to draw more specific conclusions, independent of the analysis method.

That data shows a repetition test with the same concentrations...:confused: ...on the same instrument.

Sorry that I did not make this clear.
 
Ah okay.
If we can assume the deviations are independent of the concentration, and there is no systematic difference between the two sets of measurements (unclear, but we don't have data to test this with any relevant precision), you can calculate all differences and find the standard deviation of them. This should be related to measurement uncertainties in some way. You would need more data to tell more.
 
mfb said:
Ah okay.
If we can assume the deviations are independent of the concentration, and there is no systematic difference between the two sets of measurements (unclear, but we don't have data to test this with any relevant precision), you can calculate all differences and find the standard deviation of them. This should be related to measurement uncertainties in some way. You would need more data to tell more.

Yes, we can make those assumptions.

What do you mean calculate the differences?
 
For concentration 1, take "measured value 1" - "measured value 2", repeat for all other concentrations. Something that would be 0 in the ideal case, if I understood your data.
 
mfb said:
For concentration 1, take "measured value 1" - "measured value 2", repeat for all other concentrations. Something that would be 0 in the ideal case, if I understood your data.

Oh, I see what you mean. What extra data would I need to tell more?
 
  • #10
More repetitions would certainly help.

Some uncertainties or other issues could come from details of your setup, which is impossible to estimate without knowing the setup.
 

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