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comparison of 2 values – significant

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  • #46656

    Darcy
    Participant

    Hello,
    Do you know of a test one would use to make a statement about how close a modeled value is to a known value?
    I have a known mean value of 14.54 for soil carbon. I then used a model to estimate the soil carbon value and the result was 14.14
    I would like to make a statement about how close these values are.
    Thank you for  your time and any information,
    darcy

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    #154500

    gt
    Participant

    do you want to compare two samples?

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    #154501

    gt
    Participant

    sorry i missinterprept your question
    u might want tu use 1 sample t test.
    compare one sample to a single value

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    #154502

    Darcy
    Participant

    Not really 2 different samples, but a comparison between a measured value and a modeled value. They’re quite close so I’m happy about that and want to show that a model worked well with some kind of statement of significance… But perhaps there isn’t a statistical method for this. I could just make a statement like “results show good agreement between measured and modeled values”.
    Thank you,
    darcy

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    #154513

    Adrian P. Smith
    Participant

    Hi Darcy
    I think what you would have to do is to collect mulitple soil carbon values and then model each one.
    You could then do a paired t-test to demonstrate that the difference between the measured and modeled values is not significant.
    Rgds,Adrian
    http://adrian.smith.name
     

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    #154557

    Robert Butler
    Participant

    Your use of the term “modeled value” suggest you have some kind of output (prediction) from a regression equation.  If this is the case then that equation will have an associated root mean square error (RMSE).  A very quick and dirty common practice is to take your predicted value (the modeled value) and a range of + – 2 times the RMSE around that predicted value (roughly the 95% CI) and see if your measured response falls inside those limits.  If it does then you can say that your measured and your modeled values are in agreement.

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    #154560

    Darcy
    Participant

    Thank you, I can try this.

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    #154562

    Jim Shelor
    Participant

    I think Adrain’s suggestion is a very good one.
    I would like to add one comment.  Make sure your range of samples covers you range of interest.  That way you make sure your model works across the full range with no linearity or discontinuity issues.

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    #154691

    Rajib Chatterjee
    Participant

    I have faced the same kind of problem. I got a value from the Testing machine & one from prediction model. Both are having some difference.
    Prediction Data & the Data which we are getting from any testing machine could not be same, due to the tolerance level of each procedure. Only thing which we can do is to minimize the difference between the two data.
    Solution : In my model, I have put a constant (k) which is nothing but a multiplication factor. Now while comparing the data which are from different source I use “Excel Solver” to minimize the difference between the two data.
    This gives me a very good result.
     
    Previously the difference was 0.159 or more, now it is come down to 0.0032.
     
    Regards
    Rajib Chatterjee
    Jamshedpur- India
    [email protected]
     

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