Final answer:
Without the correlation coefficient r provided, we cannot calculate the coefficient of determination. The coefficient of determination, denoted as r², represents the proportion of the variance for the dependent variable explained by an independent variable in a regression model and is found by squaring the correlation coefficient r.
Step-by-step explanation:
The student is asking how to calculate the coefficient of determination, denoted as r², which represents the proportion of the variance for the dependent variable that's explained by an independent variable in a regression model. However, to calculate r², we first need the correlation coefficient r, which has not been provided in the question. The correlation coefficient is calculated based on the paired values of the dependent and independent variables. Without the value of r, we cannot calculate r². If r is provided or calculated, we simply square it to determine r², which we then interpret in the context of the data. For instance, if r² equals 0.44 or 44%, it indicates that 44% of the variability in the dependent variable can be explained by the independent variable through the model.
The question provides some implied context about regression analysis, suggesting we're dealing with predictive modeling. Yet, without the essential statistics or additional data to calculate r, we cannot continue to determine the coefficient of determination.
.