write this as paragraphs not numbered: Statistical Methods In the study conducted by Basil-Nwoke et al. (2016), multiple regression analysis is utilized to assess the relationships among the number of dependents, community support, gender, and mental health outcomes in older adults. This statistical technique is suitable for examining the impact of multiple independent variables on a dependent variable, allowing for a simultaneous evaluation of the effects of these predictors. To ensure the robustness of the findings, it is essential that the authors check certain assumptions inherent in multiple regression analysis, as outlined by Warner (2021). These assumptions include: Linearity: The relationships between the independent and dependent variables should be linear. It would be beneficial for the authors to provide scatter plots or residual plots to demonstrate this. Independence: Observations should be independent of one another. The study design must ensure that the selection of one participant does not influence another. Homoscedasticity: The variability of the residuals should be consistent across all levels of the independent variables. The authors should report tests for this assumption, such as the Breusch-Pagan test. Normality: The residuals of the model should be normally distributed. Statistical tests (e.g., Shapiro-Wilk test) and visualizations (e.g., Q-Q plots) should confirm this. If these assumptions were adequately checked and reported, this would lend fur