Page 493 - MARSIUM'21 COMP OF PAPER

Muhammad Amirul Asraf Bin Sungip (2022)

Table 4.3: Skewness and Kurtosis Table
N Skewness Std. Error Kurtosis Std. Error
of of
Skewness Kurtosis
Valid Missing

BA1 108 0 0.113 0.233 -2.025 0.461

BA2 108 0 0.588 0.233 -0.700 0.461
BA3 108 0 -0.393 0.233 -1.384 0.461

BA4 108 0 0.159 0.233 -0.710 0.461

PQ1 108 0 0.090 0.233 1.253 0.461
PQ2 108 0 0.000 0.233 -0.108 0.461

PQ3 108 0 -0.027 0.233 -0.989 0.461
Statistics
PQ4 108 0 0.042 0.233 0.442 0.461
PV1 108 0 0.016 0.233 -0.549 0.461
PV2 108 0 0.029 0.233 0.134 0.461

PV3 108 0 0.009 0.233 0.053 0.461
PV4 108 0 0.270 0.233 -0.630 0.461
PV5 108 0 -1.283 0.233 0.686 0.461

PI1 108 0 0.018 0.233 -0.103 0.461
PI2 108 0 0.540 0.233 -0.698 0.461

PI3 108 0 0.016 0.233 -0.549 0.461
PI4 108 0 -1.114 0.233 -0.773 0.461

Brand Awareness (BA), Perceived Quality (PQ), Perceived Value (PV), Purchase Intention (PI)

4.4 Multicollinearity Analysis

Tolerance and Variance Inflation Factor (VIF) are examples of multicollinearity. The tolerance must be greater
than 0.2, according to the rule of thumb (Garson, 2012) and VIF must be less than 10 (Pallant, 2015). Table 4.4 shows all
independent variables in the Tolerance column are greater than 0.2 and fewer than 10 in the VIF column, indicating that
they are acceptable.
Table 4.4: Multicollinearity Analysis
Variables Collinearity Statistic

Tolerance VIF

Brand Awareness 4.276 1.397

Perceived Quality 0.443 1.005

Perceived Value 5.810 1.394

a. Dependent Variable: Purchase Intention

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