Having obtained the nature of the polynomial relationship, a multiple regression model was then fitted (StatsRegression Analysis →Generalized Linear Models…) to determine the parameters for the equation.
To do this a new variable (xsucros2) was calculated as the square of the sucrose concentration (Spread → Calculate →Column…).
The factor sucros was also copied into a variate xsucros so that sucrose levels could be treated as a continuous variable in the regression analysis. The output is as shown.
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***** Regression Analysis ***** Response variate: m_pgerm
Fitted terms: Constant + xsucros + xsucros2
*** Summary of analysis ***
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d.f.
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s.s.
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m.s.
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v.r.
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Regression
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2
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14955
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7477.6
|
72.78
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Residual
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45
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4623
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102.7
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Total
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47
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19579
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416.6
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*** Estimates of parameters
***
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estimate
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s.e.
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t(45)
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Constant
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3.170
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3.480
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0.91
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xsucros
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4.417
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0.465
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9.50
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xsucros2
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-0.0906
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0.0128
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-7.09
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