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Fitting a model to a data

  1. Mar 14, 2012 #1
    1. The problem statement, all variables and given/known data
    I need to fit a model to some data, where y = systolic blood pressure and x = time in weeks. The problem is, all of the 'usua' trendline options on Excel produce awful R squared values. Is there some other method I can do to fit a different sort of model that would be accurate?


    2. Relevant equations
    None that I know.


    3. The attempt at a solution
    Only thing I can put here are the graphs, but that seems a little pointless.

    Weeks (x)
    0
    1
    2
    3
    4
    5
    6
    7
    8
    9
    10
    11
    12
    13
    14
    15

    Systolic BP (mmHg) (y)
    135
    115
    130
    110
    120
    125
    130
    130
    115
    125
    120
    130
    140
    115
    125
    120

    Thanks heaps!
     
  2. jcsd
  3. Mar 14, 2012 #2
    I'm not sure anything other than a linear fit will be good. That data, from what I saw when I plotted it, is pretty scattered. That's why your R squared value is so low. You will either need more data or more precise data in order to get a better trendline.
     
  4. Mar 14, 2012 #3

    Ray Vickson

    User Avatar
    Science Advisor
    Homework Helper

    When plotted, your data looks almost random, with considerable "noise" masking the signal. That is why your R is so large---as it should be! It would be a great mistake to try to fit an accurate formula to random data.

    RGV
     
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