Download BAB III PRINT OUT 3.1 Data awal Buatlah analisis untuk permintaan

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

page
1
page
2
page
3
Document related concepts
no text concepts found
Transcript 
BAB III
PRINT OUT
3.1 Data awal
Buatlah analisis untuk permintaan sari buah dengan menggunakan uji normalitas
dan uji partial correlation.
Data penjualan permintaan sari buah di Malang tahun 2001-2015
Variable View
Data View
3.2 Output
3.2.1 Regressi
Variables Entered/Removedb
Model
1
Variables
Variables
Entered
Removed
X4, X2, X1, X3a
a. All requested variables entered.
b. Dependent Variable: Y
Method
. Enter
Model Summaryb
Model
R
Std. Error of the
Square
Estimate
R Square
.636a
1
Adjusted R
.404
.166
66.803
a. Predictors: (Constant), X4, X2, X1, X3
b. Dependent Variable: Y
ANOVAb
Model
1
Sum of Squares
df
Mean Square
Regression
30270.188
4
7567.547
Residual
44626.746
10
4462.675
Total
74896.933
14
F
Sig.
.227a
1.696
a. Predictors: (Constant), X4, X2, X1, X3
b. Dependent Variable: Y
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1
B
(Constant)
Coefficients
Std. Error
Beta
255.606
234.426
X1
.080
.184
X2
.646
X3
X4
t
Sig.
1.090
.301
.116
.433
.674
.268
.655
2.414
.036
-.119
.167
-.192
-.712
.493
-.108
.165
-.172
-.652
.529
a. Dependent Variable: Y
Residuals Statisticsa
Minimum
Predicted Value
Maximum
Mean
Std. Deviation
N
485.18
630.16
560.27
46.499
15
-106.468
64.909
.000
56.459
15
Std. Predicted Value
-1.615
1.503
.000
1.000
15
Std. Residual
-1.594
.972
.000
.845
15
Residual
a. Dependent Variable: Y
3.2.2 Deskriptif
Descriptive Statistics
Std.
Minimum Maximum Mean Deviation
N
Statistic
Unstanda
rdized
Residual
Valid N
(listwise)
Statistic
Skewness
Kurtosis
Std.
Std.
Statistic Statistic Statistic Statistic Error Statistic Error
15 -106.46759 64.90923 .000000 56.45905
0
322
-.738
.580
-.761 1.121
15
3.2.3 Uji Multikolineriatas
1. Correlinearity Statistic
Coefficientsa
Collinearity Statistics
Model
1
Tolerance
VIF
X1
.829
1.207
X2
.809
1.237
X3
.822
1.217
X4
.854
1.172
a. Dependent Variable: Y
2. Partial Correlation
Correlations
Control Variables
Y
X1
X2
X1
Correlation
X4
-.217
.046
-.363
Significance (2-tailed)
.
.456
.876
.202
df
0
12
12
12
-.217
1.000
.438
.147
.456
.
.117
.615
12
0
12
12
Correlation
.046
.438
1.000
.040
Significance (2-tailed)
.876
.117
.
.891
12
12
0
12
-.363
.147
.040
1.000
.202
.615
.891
.
12
12
12
0
Correlation
df
df
X4
X3
1.000
Significance (2-tailed)
X3
X2
Correlation
Significance (2-tailed)
df
Related documents