LANGKAH-LANGKAH UJI STATISTIK ASUMSI KLASIK DENGAN SPSS

CONTOH : DATA 3 VARIABEL α = 0,05

DATA VIEW VARIABEL VIEW

CARA KE 1 : UJI NORMALITAS Analyze, Descriptives Statistics, Explore, Plot, Normality Plots with test, Ok

KEMUDIAN TEKAN “OK” DAN HASILNYA SEPERTI INI :

Case Processing Summary

Cases

Valid Missing Total

N Percent N Percent N Percent

Promosi 10 100.0% 0 0.0% 10 100.0%

Harga 10 100.0% 0 0.0% 10 100.0%

Minat Beli 10 100.0% 0 0.0% 10 100.0%

Descriptives

Statistic Std. Error

Promosi

Mean 3.8000 .32660

95% Confidence Interval for

Mean

Lower Bound 3.0612

Upper Bound 4.5388

5% Trimmed Mean 3.8333

Median 4.0000

Variance 1.067

Std. Deviation 1.03280

Minimum 2.00

Maximum 5.00

Range 3.00

Interquartile Range 2.00

Skewness -.272 .687

Kurtosis -.896 1.334

Harga

Mean 3.4000 .33993

95% Confidence Interval for

Mean

Lower Bound 2.6310

Upper Bound 4.1690

5% Trimmed Mean 3.3889

Median 3.0000

Variance 1.156

Std. Deviation 1.07497

Minimum 2.00

Maximum 5.00

Range 3.00

Interquartile Range 1.50

Skewness .322 .687

Kurtosis -.882 1.334

Minat Beli

Mean 7.2000 .48990

95% Confidence Interval for

Mean

Lower Bound 6.0918

Upper Bound 8.3082

5% Trimmed Mean 7.1667

Median 7.0000

Variance 2.400

Std. Deviation 1.54919

Minimum 5.00

Maximum 10.00

Range 5.00

Interquartile Range 1.75

Skewness .260 .687

Kurtosis .179 1.334

Tests of Normality

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Promosi .181 10 .200* .895 10 .191

Harga .245 10 .090 .892 10 .177

Minat Beli .251 10 .073 .896 10 .197

*. This is a lower bound of the true significance.

a. Lilliefors Significance Correction

( Normal bila Sig. > α ) CARA KE 2 : Untuk Uji Kolmogorov-Smirnov Test Atau dengan cara : Analyze, Nonparametric Test, Legacy dialogs, 1-sampel K-S, Ok

DATA DIPINDAHKAN SEMUA

KEMUDIA N TEKAN OPTION, CENTANG DESKRIPTIF, CONTINUE DAN TEKAN “OK” DAN HASILNYA SEPERTI INI :

Descriptive Statistics

N Mean Std. Deviation Minimum Maximum

Promosi 10 3.8000 1.03280 2.00 5.00

Harga 10 3.4000 1.07497 2.00 5.00

Minat Beli 10 7.2000 1.54919 5.00 10.00

One-Sample Kolmogorov-Smirnov Test

Promosi Harga Minat Beli

N 10 10 10

Normal Parametersa,b

Mean 3.8000 3.4000 7.2000

Std. Deviation 1.03280 1.07497 1.54919

Most Extreme Differences

Absolute .181 .245 .251

Positive .181 .245 .251

Negative -.177 -.155 -.249

Kolmogorov-Smirnov Z .571 .775 .795

Asymp. Sig. (2-tailed) .900 .585 .553

a. Test distribution is Normal.

b. Calculated from data. HASIL SAMA DENGAN HIPOTESIS DIBAWAH

BANDINGKAN HASIL INI

DENGAN HASIL DESKRIPTIF

YG PERTAMA DIATAS,

HASILNYA AKAN SAMA

CARA KE 3 :

TEKAN OKE, DAN HASILNYA : SAMA DENGAN HASIL CARA KE 2 PADA MEAN & STANDAR DEVIASI

Estimated Distribution Parameters

Promosi Harga Minat Beli

Normal Distribution Location 3.8000 3.4000 7.2000

Scale 1.03280 1.07497 1.54919

The cases are unweighted.

Hipotesisnya :

Analyze, Nonparametric Test, one sampel, Ok

HASIL SAMA DENGAN ATAS Asymp. Sig. (2-tailed)

UJI HOMOGENITAS Analyze, Compare mean, one-way ANOVA, Options,homogeneity of variance test, continue, Ok LAKUKAN Y DENGAN X1 DULU, SETELAH CONTINUE, DAN “OK” ADA HASILNYA, LAKIUKAN KEMBALI Y DENGAN X2 Y DENGAN X1 ( Homogen bila Sig. > α )

Test of Homogeneity of Variances

Pendapatan (Y)

Levene Statistic df1 df2 Sig.

.190 2 6 .831

ANOVA

Pendapatan (Y)

Sum of Squares df Mean Square F Sig.

Between Groups 11.600 3 3.867 2.320 .175

Within Groups 10.000 6 1.667

Total 21.600 9

Y DENGAN X2

Test of Homogeneity of Variances

Pendapatan (Y)

Levene Statistic df1 df2 Sig.

1.585 3 6 .288

ANOVA

Pendapatan (Y)

Sum of Squares df Mean Square F Sig.

Between Groups 14.350 3 4.783 3.959 .071

Within Groups 7.250 6 1.208

Total 21.600 9

UJI LINIERITAS Analyze, Compare means, Means, Option, ANOVA, Test for Linierity, OK ( Linier bila Sig. > α )

KEMUDIAN “OK” DAN HASILNYA :

ANOVA Table

Sum of

Squares

df Mean Square F Sig.

Pendapatan (Y) *

Promosi (X1)

Between

Groups

(Combined) 11.600 3 3.867 2.320 .175

Linearity 11.267 1 11.267 6.760 .041

Deviation from

Linearity .333 2 .167 .100 .906

Within Groups 10.000 6 1.667

Total 21.600 9

Measures of Association

R R Squared Eta Eta Squared

Pendapatan (Y) * Promosi

(X1) .722 .522 .733 .537

ANOVA Table

Sum of

Squares

df Mean

Square

F Sig.

Pendapatan (Y) *

Harga (X2)

Between

Groups

(Combined) 14.350 3 4.783 3.959 .071

Linearity 12.062 1 12.062 9.982 .020

Deviation from

Linearity 2.288 2 1.144 .947 .439

Within Groups 7.250 6 1.208

Total 21.600 9

Measures of Association

R R Squared Eta Eta Squared

Pendapatan (Y) * Harga

(X2) .747 .558 .815 .664

DAN UJI KEDUA SECARA PARSIAL :

HASILNYA ADALAH

Correlations

Control Variables Promosi (X1) Harga (X2) Pendapatan (Y)

-none-a

Promosi (X1)

Correlation 1.000 .080 .722

Significance (2-tailed) . .826 .018

Df 0 8 8

Harga (X2)

Correlation .080 1.000 .747

Significance (2-tailed) .826 . .013

Df 8 0 8

Pendapatan (Y)

Correlation .722 .747 1.000

Significance (2-tailed) .018 .013 .

Df 8 8 0

Pendapatan (Y)

Promosi (X1)

Correlation 1.000 -1.000

Significance (2-tailed) . .000

Df 0 7

Harga (X2)

Correlation -1.000 1.000

Significance (2-tailed) .000 .

Df 7 0

a. Cells contain zero-order (Pearson) correlations.

UJI MULTIKOLINIERITAS Analyze, Regresi, Linier, Statistic, Colinierity diagnostic, Ok.

SETELAH KLIK CONTINUE, TEKAN “OK”, MAKA HASILNYA :

Coefficientsa

Model Collinearity Statistics

Tolerance VIF

1 Promosi (X1) .994 1.006

Harga (X2) .994 1.006

a. Dependent Variable: Pendapatan (Y)

Collinearity Diagnosticsa

Model Dimension Eigenvalue Condition Index Variance Proportions

(Constant) Promosi (X1) Harga (X2)

1

1 2.906 1.000 .00 .01 .01

2 .068 6.555 .01 .37 .70

3 .026 10.571 .99 .62 .29

a. Dependent Variable: Pendapatan (Y)

( bila nilai Tolerance dan VIF mendekati 1 ) UJI HETEROKEDASTATISTIK Analyze, Regresi, Linier, Plot, SRESID pada Y, ZPRED pada X, Ok.

SETELAH KLIK CONTINUE, KLIK “OK” MAKA HASILNYA :

Residuals Statisticsa

Minimum Maximum Mean Std. Deviation N

Predicted Value 5.00 10.00 7.20 1.549 10

Residual .000 .000 .000 .000 10

Std. Predicted Value -1.420 1.807 .000 1.000 10

Std. Residual .000 .000 .000 .000 10

a. Dependent Variable: Pendapatan (Y)

UJI AUTOKORELASI (bila ada 2 error) Analyze, Regresi, Linier, Statistic, Durbin-Watson, Ok

SETELAH TEKAN CONTINUE, KLIK “OK”, MAKA HASILNYA :

Model Summaryb

Model R R Square Adjusted R

Square

Std. Error of the

Estimate

Durbin-Watson

1 1.000a 1.000 1.000 .000 .076

a. Predictors: (Constant), Harga (X2), Promosi (X1)

b. Dependent Variable: Pendapatan (Y)

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 21.600 2 10.800 . .b

Residual .000 7 .000

Total 21.600 9

a. Dependent Variable: Pendapatan (Y)

b. Predictors: (Constant), Harga (X2), Promosi (X1)

Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1

(Constant) 4.831E-016 .000 .000 1.000

Promosi (X1) 1.000 .000 .667 224141999.254 .000

Harga (X2) 1.000 .000 .694 233294389.450 .000

a. Dependent Variable: Pendapatan (Y)

UJI REGRESI LINIER BERGANDA Analyze, regression, Linier, Statistic, Estimate, Model Fit, R Square, Descriptive, Part & Partial Correlation, Ok.

SETELAH TEKAN CONTINUE, KLIK “OK”, MAKA HASILNYA :

Correlations

Pendapatan (Y) Promosi (X1) Harga (X2)

Pearson Correlation

Pendapatan (Y) 1.000 .722 .747

Promosi (X1) .722 1.000 .080

Harga (X2) .747 .080 1.000

Sig. (1-tailed)

Pendapatan (Y) . .009 .006

Promosi (X1) .009 . .413

Harga (X2) .006 .413 .

N

Pendapatan (Y) 10 10 10

Promosi (X1) 10 10 10

Harga (X2) 10 10 10

Model Summaryb

Model R R Square Adjusted R

Square

Std. Error of

the Estimate

Change Statistics

R Square

Change

F Change df1 df2 Sig. F

Change

1 1.000a 1.000 1.000 .000 1.000 . 2 7 .

a. Predictors: (Constant), Harga (X2), Promosi (X1)

b. Dependent Variable: Pendapatan (Y)

ANOVAa

Model Sum of Squares df Mean Square F Sig.

1

Regression 21.600 2 10.800 . .b

Residual .000 7 .000

Total 21.600 9

a. Dependent Variable: Pendapatan (Y)

b. Predictors: (Constant), Harga (X2), Promosi (X1)

Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig. Correlations

B Std.

Error

Beta Zero-

order

Partial Part

1

(Constant) 4.831E-016 .000 .000 1.000

Promosi (X1) 1.000 .000 .667 224141999.254 .000 .722 1.000 .665

Harga (X2) 1.000 .000 .694 233294389.450 .000 .747 1.000 .692

a. Dependent Variable: Pendapatan (Y)

DESKRIPSI DATA (CONTOH 2 VARIABEL ) ANALYZE, DESCRIPTIVE, FREQUENCIES, OK.

SELURUH NOMOR ITEM ANGKET, KEMUDIAN TEKAN “OK” DAN HASILNYA :

angket a1

Frequency Percent Valid Percent Cumulative

Percent

Valid

2 1 10.0 10.0 10.0

3 3 30.0 30.0 40.0

4 3 30.0 30.0 70.0

5 3 30.0 30.0 100.0

Total 10 100.0 100.0

DAN SETERUSNYA SEMUA ANGKET

UJI VALIDITAS ( DIUJI MASING-MASING VARIABEL )

ANALYZE, CORRELATE, BIVARIATE, PINDAHKAN SEMUA ITEM ANGKET , PILIH

SPEARMAN ATAU PEARSON, OK.

HASILNYA :

Correlations VARIABEL X

angket a1 angket a2 Total A

Spearman's rho

angket a1

Correlation Coefficient 1.000 .026 .734*

Sig. (2-tailed) . .943 .016

N 10 10 10

angket a2

Correlation Coefficient .026 1.000 .683*

Sig. (2-tailed) .943 . .030

N 10 10 10

Total A

Correlation Coefficient .734* .683

* 1.000

Sig. (2-tailed) .016 .030 .

N 10 10 10

*. Correlation is significant at the 0.05 level (2-tailed).

SETELAH MENGUJI VARIABEL X, KEMUDIAN UJI VARIABEL Y

UJI RELIABILITAS

UNTUK UJI RELIABILITAS DENGAN SPLIT HALF, MAKA DIJUMLAHKAN ITEM X

GANJIL DENGAN ITEM Y GANJIL, DAN ITEM GENAP X DENGAN ITEM GENAP Y,

( GANJIL X + GANJIL Y = TOTAL GANJIL ) DAN ( GENAP X + GENAP Y = TOTAL

GENAP), MAKA KORELASIKAN TOTAL GANJIL DENGAN TOTAL GENAP,

LANGKAHNYA SAMA DENGAN UJI KORELASI DIATAS, YANG MEMBEDAKAN

ADALAH DATANYA YANG DIKORELASIKAN.

UJI KORELASI PRODUCT MOMENT

UJI REGRESI LINIER SEDERHANA

PILIH SPEARMAN ATAU PERSON, YANG SESUAI DENGAN HASIL MANUAL

Correlations

Total A Total B

Spearman's rho

Total A

Correlation Coefficient 1.000 .386

Sig. (2-tailed) . .271

N 10 10

Total B

Correlation Coefficient .386 1.000

Sig. (2-tailed) .271 .

N 10 10

Correlations

Total A Total B

Total A

Pearson Correlation 1 .371

Sig. (2-tailed) .291

N 10 10

Total B

Pearson Correlation .371 1

Sig. (2-tailed) .291

N 10 10

UJI REGRESI LINIER SEDERHANA

Model Summaryb

Model Change Statistics

R Square

Change

F Change df1 df2 Sig. F Change

1 .138a 1.280 1 8 .291

a. Predictors: (Constant), Total A

b. Dependent Variable: Total B

Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 5.833 1.864 3.129 .014

Total A .287 .254 .371 1.131 .291

a. Dependent Variable: Total B