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Power regression for a specific function with data

  1. 03-01-2018, 10:38 AM #1
    NocturnalSheep is offline
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    Power regression for a specific function with data

    I am currently working with data from a physics experiment, and I just made power regression. I get a function from it, something like
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    The coefficient of determination is of course 1 because it is power regression, but what I really want is to know how well my data fits the specific function
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    Is there a way of making Excel find the coefficient of determination for how well my data fits that specific model?

    English is not my first language, please excuse any errors.
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  2. 03-01-2018, 11:07 AM #2
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    Re: Power regression for a specific function with data

    insert a graph, build trend line and show its equation
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  3. 03-01-2018, 11:27 AM #3
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    Re: Power regression for a specific function with data

    Well, I know how to build a trendline (by the way, the one you sent me is polynomial regression, and in that case the coefficient of determination will not always be 1), but is it possible to make excel give me a coefficient of determination based on my specific function and not the one from the power regression?
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  4. 03-01-2018, 11:52 AM #4
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    Re: Power regression for a specific function with data

    I don't understand the question.

    You have some data which you regressed to your first equation, and then say R2 is 1 "because it is a power regression". You mean the regression is a perfect fit to data? Seems unlikely.

    Then you want to know R2 between the first formula and y=x^3?
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  5. 03-01-2018, 12:32 PM #5
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    Re: Power regression for a specific function with data

    Maybe this:

    A
    B
    C
    D
    E
    F
    1
    x
    1.00012 * x ^2.9998
    x^3
    2
    0
    0.00000
    0.00000
    0.999999999194346
    		 E2: =RSQ(B2:B12, C2:C12)
    3
    0.1
    0.00100
    0.00100
    4
    0.2
    0.00800
    0.00800
    5
    0.3
    0.02701
    0.02700
    6
    0.4
    0.06402
    0.06400
    7
    0.5
    0.12503
    0.12500
    8
    0.6
    0.21605
    0.21600
    9
    0.7
    0.34307
    0.34300
    10
    0.8
    0.51208
    0.51200
    11
    0.9
    0.72910
    0.72900
    12
    1
    1.00012
    1.00000
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