1. Suppose that you have several hypotheses to test, as follow:

H1: Service quality has a significant positive relationship with customer satisfaction.

H2: Perceived risk has a significant negative relationship with customer satisfaction.

H3: Brand trust has a significant positive relationship with customer satisfaction.

H4: Product variety has a significant positive relationship with customer satisfaction.

H5: Store atmosphere has a significant positive relationship with customer satisfaction.

After you analyze the data using linear regression analysis, the result showed as follow:

Model Summary Adjusted R Std. Error of Model R R Square Square the Estimate 1 .633 .473 .482 822ANOVA Sum of Model Squares df Mean Square F Sig. Regression 87.200 6 14.533 21.527 000 Residual 130.300 193 .675 Total 217.500 199Coefficients Unstandardized Standardized Coefficients Coefficients Model B Std. Error Beta Sig. 1 (Constant) 1.847 .659 2.805 .006 Service Quality .130 .146 .113 893 .373 Perceived Risk .201 077 .390 3.896 .010 Brand Trust .340 .112 .037 1.655 .053 Product Variety -.211 083 -.229 -3.330 .006 Store Atmosphere .225 .089 .260 2.513 .013 a. Dependent Variable: Customer Satisfaction