Regression Analysis For A Dependence Method - 753 Words

Regarding the testing of the hypotheses of this research, regression analysis or structural equation modelling techniques is best suited for a dependence method (Hair et al., 2014). We employed regression analysis to specify the extent to which the independent variables predicted the dependent variable. The analysis conducted in this study was therefore intended to test the hypotheses of the study. The regression output provided some measures which allow assessment of the hypotheses. Following from the hypotheses, Brand Engagement was used as the dependent variable while the independent variables consisted of Monetary Savings, Exploration, Entertainment, Recognition, and Social Benefit. Results from the model assessment are presented in the Table VI. Insert table VI Results from the model assessment indicate strong and significant reliabilities among the constructs used in the study (F = 87.362, Prob.F-stats 0.001). This was followed by Exploration (ÃŽ ² = 0.102, t = 2.271, P = 0.024 0.05), as well as Entertainment (ÃŽ ² = 0.081, t = 1.712, P = 0.068 0.10). Although Recognition was positively related to Brand Engagement, it was not statistically significant (ÃŽ ² = 0.051, t = 1.084, P = 0.279 0.05). It was however discovered that Monetary savings was inversely related to Brand Engagement (ÃŽ ² = -.009, t = -0.194) as well as statistically not significant in the current study (P = 0.846 0.05). In consequence, hypotheses one and four (H1 and H4) were rejected in our studyShow MoreRelatedSmoothing Dat The Estition Of Variance In Data890 Words   |  4 PagesESTIMATION OF VARIANCE IN HETEROSCEDASTIC DATA Abstract Data which exhibit none constant variance is considered. Smoothing procedures are applied to estimate these none constant variances. In these smoothing methods the problem is to establish how much to smooth. The choice of the smoother and the choice of the bandwidth are explored. 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