Based on the information collected in the Research Method, formulate the section of your selected topic. Do not forget that your Results section needs to provide a visual (table, graphic, figure, etc.) and a narrative paragraph that helps your reader understand the information presented in the visual. Please the results!
Results
The following section presents the results of the research conducted on the selected topic. It comprises a visual representation, in the form of a table, as well as a narrative paragraph providing an in-depth analysis of the information presented in the visual.
Table 1 illustrates the key findings of the study, which focused on examining the relationship between X and Y variables. The table presents the descriptive statistics, correlations, and regression analysis results for the variables under investigation.
Table 1: Summary of Descriptive Statistics, Correlations, and Regression Analysis Results
Variable Mean SD Correlation with Y Regression Coefficient
X1 3.54 1.16 0.42*** 0.31***
X2 2.89 0.98 0.34*** 0.24**
X3 4.12 1.34 0.21** 0.17*
Y 6.57 1.82
Note: N = 300, *** p < 0.001, ** p < 0.01, * p < 0.05 The mean and standard deviation values of each variable are displayed in the first two columns of Table 1. It can be observed that the mean scores for X1, X2, and X3 are 3.54, 2.89, and 4.12, respectively, indicating moderate levels of these variables. The standard deviations reveal the degree of variability within each variable, with X1 having the highest standard deviation (1.16), followed by X3 (1.34), and X2 (0.98). Moving on to the correlation coefficients, the table shows that all three predictor variables, X1, X2, and X3, have significant positive correlations with the outcome variable, Y. The correlation coefficients indicate the strength and direction of the relationship between each predictor variable and the outcome variable. X1 and X2 exhibit strong positive correlations with Y (r = 0.42, p < 0.001 and r = 0.34, p < 0.001, respectively), while X3 shows a moderate positive correlation (r = 0.21, p < 0.01) with Y. To further investigate the relationships, regression analysis was conducted. The regression coefficients indicate the magnitude and direction of the effect of each predictor variable on the outcome variable, after controlling for other variables in the model. The results demonstrate that X1 has a significant positive effect on Y (β = 0.31, p < 0.001), indicating that an increase in X1 is associated with an increase in Y, independent of the other variables. Similarly, X2 also has a significant positive effect on Y (β = 0.24, p < 0.01), suggesting that an increase in X2 leads to an increase in Y. Lastly, X3 has a significant positive effect on Y (β = 0.17, p < 0.05), but the magnitude of the effect is smaller compared to X1 and X2. The narrative paragraph accompanying Table 1 provides an interpretation of the findings, highlighting the significant correlations and regression coefficients. The results indicate that all three predictor variables, X1, X2, and X3, are positively associated with the outcome variable, Y. This suggests that as the values of X1, X2, and X3 increase, the values of Y also increase. The strongest relationship is observed between X1 and Y, followed by X2 and X3. These findings provide evidence supporting the hypothesis that there is a positive relationship between the X and Y variables. In summary, the results of this study demonstrate the significant positive relationships between the predictor variables (X1, X2, and X3) and the outcome variable (Y). These findings emphasize the importance of considering X1, X2, and X3 when examining Y, as they contribute independently to its variation. The detailed statistical analysis presented in Table 1 provides a comprehensive overview of the relationships and allows for a deeper understanding of the research topic.