Interpreting a Factor Analysis - Essay Example

Test Validity: The Relationship between Age and the Tendency for Dependence Hypothesis This is a test of the validity of the dependency scale based on information on age and the six items of financial dependency in the data (moneydata.sav). According to Gupta (2007), the theoretical relationship between age and financial dependency is hedged on several factors, some ideological and some sociological. For instance, the author notes that young people in their adolescence (presumably represented by the group aged 18 – 20 in this study) are more likely to have a lower education compared to the older individuals in their late twenties and beyond.

This low education affects their ability to either secure any or a well-paying job (Vijayakumar, 2013). Furthermore, the younger generations have lower job skills and work experience compared to the older persons. Due to their limited access to work/ well paying work, young people are more prone to poverty and, consequently, higher financial dependency (Gupta, 2007). These two studies successfully demonstrate that there is a relationship between age and dependency – the higher the age, the lower the level of dependency.

Based on these findings, I seek to investigate whether this hypothetical relationship between age and financial dependency is valid for the data at hand. The following hypothesis is investigated:H0: There exists negative correlation between age and financial dependency. That implies that, for this study, higher levels of dependency are expected to correspond to lower ages. A bivariate correlation analysis was run in the SPSS using the computed value for “dependency” and age. The test was run at the 5% level of significance.

The findings are contained in the following section.ResultsTable 1: Descriptive StatisticsMeanStd. DeviationNParticipants age32.9011.2501146Dependence14.24874.557071146Table 2: CorrelationsParticipants ageDependenceParticipants agePearson Correlation1-0.107**Sig. (2-tailed)0.000N11461146DependencePearson Correlation-0.107**1Sig. (2-tailed)0.000N11461146**. Correlation is significant at the 0.01 level (2-tailed). The average ages of the 1146 participants is 32.4 years (Std. dev. = 11.25), while the average dependency score is 14.25 (Std. dev. = 4.56).

The correlation between the ages of participants and dependency is -0.107 (p < 0.001). The p-value (p < 0.001) confirms that the correlation is indeed significant, and, therefore, our hypothesis is true.Conclusion The findings of this study fall in line with the findings of both Gupta (2007) and Vijavakumar (2013) which established the existence of significant correlations between the ages and dependency levels of participants. This confirms validity of the “dependency” scale. Since the relationship between age and dependency is inverse (negative correlation coefficient), and having confirmed the validity of the dependency scale, we conclude that the older generations have relatively lower levels of financial dependency, while the younger individuals have relatively higher levels of financial dependency.

ReferencesGupta, S. (2007). Autonomy, dependency, or display? The relationship between married women’s earnings and housework. Journal of Marriage and Family. 69: 399-417.Vijayakumar, S. (2013). An empirical study on the nexus of poverty, GDP growth, dependency ratio and employment in developing countries. Journal of Competitiveness. 5(2): 67-82. ISSN: 1804-171X.