Agriculture Reference
In-Depth Information
This results in the following output:
Number of obs = 54 R-squared = 0.9426
Root MSE = 729.623 Adj R-squared = 0.8311
Source | Partial SS df MS F Prob > F
------------+--------------------------------------------------
Model | 157423365 35 4497810.44 8.45 0.0000
|
rep | 9906491.23 2 4953245.62 5.83 0.0210
var | 7133423.66 5 1426684.73 1.68 0.2271
var#rep | 8500280.86 10 850028.086
------------+--------------------------------------------------
fert | 49718951.4 1 49718951.4 38.51 0.0250
fert#rep | 2582254.39 2 1291127.19
------------+--------------------------------------------------
var*fert | 21478590.5 5 4295718.09 17.90 0.0001
rep*var*fert| 2399786.28 10 239978.628
------------+--------------------------------------------------
|
Residual | 9582283.5 18 532349.083
------------+--------------------------------------------------
Total | 167005649 53 3151049.98
In this analysis, as in the previous, the fertilizer rate is significant
(Prob>F) at 0.0250. This also tells us, however, that the effect of the
fertilizer application was a linear effect.
Another approach is to drop the last term and do the analysis again.
Enter the following and see the results:
anova
yield rep var
/
var
#
rep fert
/
fert
#
rep var
#
fert
Number of obs = 54 R-squared = 0.9507
Root MSE = 641.596 Adj R-squared = 0.8694
Source | Partial SS df MS F Prob > F
-------------+----------------------------------------------------
Model | 158772732 33 4811294.9 11.69 0.0000
|
rep | 9220962.33 2 4610481.17 3.09 0.0902
var | 57100201.3 5 11420040.3 7.65 0.0034
var#rep | 14922619.2 10 1492261.92
-------------+----------------------------------------------------
fert | 50676061.4 2 25338030.7 34.07 0.0031
fert#rep | 2974907.89 4 743726.972
-------------+----------------------------------------------------
var#fert | 23877979.4 10 2387797.94 5.80 0.0004
|
Residual | 8232917.22 20 411645.861
-------------+----------------------------------------------------
Total | 167005649 53 3151049.98
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