Table 1 indicates the descriptive statistics for both the dependent and independent variables. The means of variables, cost, age, risk, and satisfaction include $14906.51, 73.25 years, 5.69, and 50.02. The sample size used was 185.
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| Table 2: Correlations | |||||
| cost | age | risk | satisfaction | ||
| Pearson Correlation | cost | 1.000 | .279 | .199 | -.071 |
| age | .279 | 1.000 | .152 | .094 | |
| risk | .199 | .152 | 1.000 | .037 | |
| satisfaction | -.071 | .094 | .037 | 1.000 | |
| Sig. (1-tailed) | cost | . | .000 | .003 | .169 |
| age | .000 | . | .019 | .101 | |
| risk | .003 | .019 | . | .307 | |
| satisfaction | .169 | .101 | .307 | . | |
| N | cost | 185 | 185 | 185 | 185 |
| age | 185 | 185 | 185 | 185 | |
| risk | 185 | 185 | 185 | 185 | |
| satisfaction | 185 | 185 | 185 | 185 | |
Table 2 shows the correlation between dependent and independent variables. The outcomes show that there is a weak positive correlation between the cost and age; the correlation coefficient is 0.279. The correlation between cost and risk is also weak and positive; the correlation coefficient is 0.199. Finally, the correlation between cost and the level of satisfaction is weak and negative; the correlation coefficient is -.071.
| Table 3: Model Summary | |||||||||
| 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 | .336a | .113 | .098 | 2482.429 | .113 | 7.692 | 3 | 181 | .000 |
| a. Predictors: (Constant), satisfaction, risk, age | |||||||||
From table 3, the R-Square is 0.113 showing a “Medium” effect size; therefore, the model attempt to explain much of the variance in the dependent variable. The significant value from the analysis is 0.000 < 0.05; therefore, we reject that null hypothesis and conclude that the model is fit or significant. Given that the analysis was done at 95% level of significance, the null hypothesis is rejected when the significant values obtained are less than 0.05.
| Table 4: Coefficientsa | ||||||||
| Model | Unstandardized Coefficients | Standardized Coefficients | t | Sig. | 95.0% Confidence Interval for B | |||
| B | Std. Error | Beta | Lower Bound | Upper Bound | ||||
| 1 | (Constan) | 6652.176 | 2096.818 | 3.173 | .002 | 2514.825 | 10789.527 | |
| age | 107.036 | 28.911 | .263 | 3.702 | .000 | 49.990 | 164.082 | |
| risk | 153.557 | 66.685 | .163 | 2.303 | .022 | 21.978 | 285.136 | |
| satisfaction | -9.195 | 6.358 | -.102 | -1.446 | .150 | -21.740 | 3.351 | |
| a. Dependent Variable: cost | ||||||||
From table 4, there is the indication of different unstandardized coefficients for the independent variables used in the study. A regression equation can therefore be formulated from the information given. Using the equation of
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