Statistical modelling/Multiple regression analysis

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.

 
***** Regression Analysis *****
Response variate: m_pgerm
Fitted terms: Constant + xsucros + xsucros2

*** Summary of analysis ***

d.f.

s.s.

m.s.

v.r.

Regression

2

14955

7477.6

72.78

Residual

45

4623

102.7

 
Total

47

19579

416.6

 
*** Estimates of parameters ***

estimate

s.e.

t(45)

Constant

3.170

3.480

0.91

xsucros

4.417

0.465

9.50

xsucros2

-0.0906

0.0128

-7.09

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