ANNEXE Q : Résultat de l'analyse
économétrique sur SPSS pour le type I
Correlations
|
Pearson
Correlation
|
|
Q
|
Z1
|
Z2
|
Z3
|
|
Q
|
1.000
|
-.726
|
.744
|
.710
|
|
Z1
|
-.726
|
1.000
|
-.296
|
-.337
|
|
Z2
|
.744
|
-.296
|
1.000
|
.463
|
|
Z3
|
.710
|
-.337
|
.463
|
1.000
|
Model Summaryb
|
Mode
|
R
|
R
Square
|
Adjusted R Square
|
Std.
Error of
the
Estimate
|
Change Statistics
|
|
R
Square
Change
|
F
Change
|
df1
|
df2
|
Sig. F
Change
|
|
1
|
.960
a
|
.921
|
.897
|
4.151
|
.921
|
38.942
|
3
|
10
|
.000
|
a Predictors: (Constant), Z3, Z2, Z1
b Dependent Variable: Q
ANOVAb
|
Model
|
Sum of
Squares
|
df
|
Mean Square
|
F
|
Sig.
|
|
1 Regression
|
2012.585
|
3
|
670.862
|
38.942
|
.000 a
|
|
Residual
|
172.272
|
10
|
17.227
|
|
|
|
Total
|
2184.857
|
13
|
|
|
|
a Predictors: (Constant), Z3, Z2, Z1
b Dependent Variable: Q
24
|
Model
|
Unstandardized
Coefficients
|
Standardized
Coefficients
|
t
|
Sig.
|
95% Confidence
Interval for B
|
Correlations
|
Collinearity
Statistics
|
|
B
|
Std.
Error
|
Beta
|
Lower
Bound
|
Upper
Bound
|
Zero-order
|
Partial
|
Part
|
Tolerance
|
VIF
|
|
1(Constant)
|
54.052
|
12.502
|
|
4.323
|
.002
|
26.196
|
81.908
|
|
|
|
|
|
|
Z1
|
-88.749
|
17.706
|
-.480
|
-
5.012
|
.001
|
-
128.201
|
-
49.298
|
-.726
|
-.846
|
-.445
|
.862
|
1.161
|
|
Z2
|
8.929E-
04
|
.000
|
.443
|
4.359
|
.001
|
.000
|
.001
|
.744
|
.809
|
.387
|
.763
|
1.310
|
|
Z3
|
2.685E-
02
|
.008
|
.343
|
3.325
|
.008
|
.009
|
.045
|
.710
|
.725
|
.295
|
.742
|
1.348
|
Coefficientsa
a Dependent Variable: Q
Coefficient Correlationsa
|
Mode
|
Z3
|
Z2
|
Z1
|
|
1
|
Correlations
|
Z3
|
1.000
|
.236
|
-.404
|
|
Z2
|
.236
|
1.000
|
.168
|
|
Z1
|
-.404
|
.168
|
1.000
|
|
Covariances
|
Z3
|
6.523E-05
|
3.370E-02
|
-6.689E-07
|
|
Z2
|
3.370E-02
|
313.501
|
6.100E-04
|
|
Z1
|
-6.689E-07
|
6.100E-04
|
4.197E-08
|
a Dependent Variable: Q
25
Collinearity Diagnosticsa
|
Model
|
Dimension
|
Eigenvalue
|
Condition
Index
|
Variance Proportions
|
|
(Constant)
|
Z1
|
Z2
|
Z3
|
|
1
|
1
|
3.624
|
1.000
|
.00
|
.00
|
.02
|
.00
|
|
2
|
.336
|
3.284
|
.00
|
.00
|
.73
|
.00
|
|
3
|
3.552E-02
|
10.101
|
.01
|
.09
|
.24
|
.74
|
|
4
|
4.858E-03
|
27.312
|
.99
|
.91
|
.01
|
.26
|
a Dependent Variable: Q
Casewise Diagnosticsa
|
Case Number
|
Std. Residual
|
Q
|
Predicted Value
|
Residual
|
|
1
|
-.743
|
16
|
19.08
|
-3.08
|
|
2
|
-.533
|
42
|
44.21
|
-2.21
|
|
3
|
1.195
|
25
|
20.04
|
4.96
|
|
4
|
-.251
|
14
|
15.04
|
-1.04
|
|
5
|
-.857
|
27
|
30.56
|
-3.56
|
|
6
|
.907
|
16
|
12.23
|
3.77
|
|
7
|
.024
|
32
|
31.90
|
.10
|
|
8
|
.701
|
22
|
19.09
|
2.91
|
|
9
|
-.270
|
18
|
19.12
|
-1.12
|
|
10
|
.827
|
45
|
41.57
|
3.43
|
|
11
|
-1.817
|
28
|
35.54
|
-7.54
|
|
12
|
-.066
|
35
|
35.27
|
-.27
|
|
13
|
1.207
|
60
|
54.99
|
5.01
|
|
14
|
-.323
|
30
|
31.34
|
-1.34
|
a Dependent Variable: Q
26
Histogram
Dependent Variable: Quantité de Bambous Planté
|
Frequency
|
6 5 4 3 2
1
0
|
|
Std. Dev = .88 Mean = 0.00 N = 14.00
|
-2.00 -1.50 -1.00 -.50 0.00 .50 1.00
Regression Standardized Residual
Normal P-P Plot of Regression Standar Dependent Variable:
Quantité de Bamb
Expected Cum P rob
0.00
1.00
.75
.50
.25
0.00 .25 .50 .75 1.00
Observed Cum Prob
27
Partial Regression Plot
Dependent Variable: Quantité de Bambous Plant
Quantité de Bambous Plantée
-10
10
0
-300 -200 -100 0 100 200 300
Revenu Bambou 2005
Partial Regression Plot
Dependent Variable: Quantité de Bambous Plant
Quantité de Bambous Plantée
-10
-20
20
10
0
-10000 0 10000 20000
Revenu non agricole
28
Partial Regression Plot
Dependent Variable: Quantité de Bambous Plant
Quantité de Bambous Plantée
-10
-20
20
10
0
-.2 -.1 0.0 .1 .2
Taux d'autoconsommation
29
| 
