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The regression analysis found a perfect linear relationship between the variables Penjualan (sales), Promosi (promotions), and Produksi (production) with an R-square of 1.000. The model was statistically significant and found that Promosi and Produksi can be used to perfectly predict Penjualan. Tolerance values reached the limit, so influence statistics could not be computed.

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69 views6 pages

Output

The regression analysis found a perfect linear relationship between the variables Penjualan (sales), Promosi (promotions), and Produksi (production) with an R-square of 1.000. The model was statistically significant and found that Promosi and Produksi can be used to perfectly predict Penjualan. Tolerance values reached the limit, so influence statistics could not be computed.

Uploaded by

ANNISA
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as RTF, PDF, TXT or read online on Scribd
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Your temporary usage period for IBM SPSS Statistics will expire in 6151 days.

NEW FILE.
DATASET NAME DataSet1 WINDOW=FRONT.
REGRESSION
/DESCRIPTIVES MEAN STDDEV CORR SIG N
/MISSING LISTWISE
/STATISTICS COEFF OUTS CI(95) R ANOVA COLLIN TOL CHANGE ZPP
/CRITERIA=PIN(.05) POUT(.10)
/NOORIGIN
/DEPENDENT Penjualan
/METHOD=ENTER Promosi Harga Produksi
/RESIDUALS DURBIN.

Regression

Notes
Output Created 27-FEB-2019 06:40:28
Comments
Input Active Dataset DataSet1
Filter <none>
Weight <none>
Split File <none>
N of Rows in Working Data 30
File
Missing Value Handling Definition of Missing User-defined missing values
are treated as missing.
Cases Used Statistics are based on cases
with no missing values for
any variable used.
Syntax REGRESSION
/DESCRIPTIVES MEAN
STDDEV CORR SIG N
/MISSING LISTWISE
/STATISTICS COEFF OUTS
CI(95) R ANOVA COLLIN
TOL CHANGE ZPP
/CRITERIA=PIN(.05)
POUT(.10)
/NOORIGIN
/DEPENDENT Penjualan
/METHOD=ENTER Promosi
Harga Produksi
/RESIDUALS DURBIN.
Resources Processor Time 00:00:00,03
Elapsed Time 00:00:00,39
Memory Required 3472 bytes
Additional Memory Required 0 bytes
for Residual Plots

[DataSet1]

Warnings
For the final model with dependent variable Penjualan (unit),
influence statistics cannot be computed because the fit is perfect.

Descriptive Statistics
Mean Std. Deviation N
Penjualan (unit) 20.0667 11.20324 30
Promosi (kali)) 22.1333 11.47030 30
Harga (rupiah) 20066.6667 11203.24255 30
Produksi (unit) 21.0667 11.20324 30
Correlations
Penjualan (unit) Promosi (kali)) Harga (rupiah)
Pearson Correlation Penjualan (unit) 1.000 .994 .
Promosi (kali)) .994 1.000 .994
Harga (rupiah) . .994 1.000
Produksi (unit) 1.000 .994 .
Sig. (1-tailed) Penjualan (unit) . .000 .000
Promosi (kali)) .000 . .000
Harga (rupiah) .000 .000 .
Produksi (unit) .000 .000 .000
N Penjualan (unit) 30 30 30
Promosi (kali)) 30 30 30
Harga (rupiah) 30 30 30
Produksi (unit) 30 30 30

Correlations
Produksi (unit)
Pearson Correlation Penjualan (unit) 1.000
Promosi (kali)) .994
Harga (rupiah) .
Produksi (unit) 1.000
Sig. (1-tailed) Penjualan (unit) .000
Promosi (kali)) .000
Harga (rupiah) .000
Produksi (unit) .
N Penjualan (unit) 30
Promosi (kali)) 30
Harga (rupiah) 30
Produksi (unit) 30

Variables Entered/Removeda
Variables Variables
Model Entered Removed Method
1 Produksi (unit), . Enter
Promosi (kali))b

a. Dependent Variable: Penjualan (unit)


b. Tolerance = .000 limit reached.

Model Summaryc
Change Statistics
Adjusted R Std. Error of the R Square
Model R R Square Square Estimate Change F Change df1
a
1 1.000 1.000 1.000 .00000 1.000 . 2

Model Summaryc
Change Statistics
Model df2 Sig. F Change
1 27 . .b

a. Predictors: (Constant), Produksi (unit), Promosi (kali))


b. Not computed because there is no residual variance.
c. Dependent Variable: Penjualan (unit)

ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 3639.867 2 1819.933 . .b
Residual .000 27 .000
Total 3639.867 29

a. Dependent Variable: Penjualan (unit)


b. Predictors: (Constant), Produksi (unit), Promosi (kali))

Coefficientsa
Standardized
Unstandardized Coefficients Coefficients
Model B Std. Error Beta t Sig.
1 (Constant) -1.000 .000 . .
Promosi (kali)) .000 .000 .000 . .
Produksi (unit) 1.000 .000 1.000 . .

Coefficientsa
Model 95,0% Confidence Interval for B Correlations
Lower Bound Upper Bound Zero-order Partial Part
1 (Constant) -1.000 -1.000
Promosi (kali)) .000 .000 .994 1.000 .000
Produksi (unit) 1.000 1.000 1.000 1.000 .106

Coefficientsa
Collinearity Statistics
Model Tolerance VIF
1 (Constant)
Promosi (kali)) .011 89.408
Produksi (unit) .011 89.408

a. Dependent Variable: Penjualan (unit)

Excluded Variablesa
Partial Collinearity Statistics
Model Beta In t Sig. Correlation Tolerance VIF
1 Harga (rupiah) .b . . . .000 .

Excluded Variablesa
Collinearity Statistics
Model Minimum Tolerance
1 Harga (rupiah) .000

a. Dependent Variable: Penjualan (unit)


b. Predictors in the Model: (Constant), Produksi (unit), Promosi (kali))

Collinearity Diagnosticsa
Variance Proportions
Model Dimension Eigenvalue Condition Index (Constant) Promosi (kali)) Produksi (unit)
1 1 2.852 1.000 .02 .00 .00
2 .147 4.402 .93 .00 .00
3 .001 49.178 .05 1.00 1.00

a. Dependent Variable: Penjualan (unit)


Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 2.0000 40.0000 20.0667 11.20324 30
Residual .00000 .00000 .00000 .00000 30
Std. Predicted Value -1.613 1.779 .000 1.000 30
Std. Residual . . . . 0

a. Dependent Variable: Penjualan (unit)

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