Final answer:
The coefficient of determination (r^2) is calculated by squaring the correlation coefficient (r), and represents the proportion of variance for a dependent variable that's explained by an independent variable in a regression model. The value of SST cannot determine r^2 without the correlation coefficient (r).
Step-by-step explanation:
The question relates to the concept of correlation and the coefficient of determination, specifically how to find the coefficient of determination (r2) given the value of the total sum of squares (SST). Unfortunately, the value of SST alone is not sufficient to determine the coefficient of determination. To calculate r2, you need the correlation coefficient (r), which is not provided in the question. The coefficient of determination is calculated by squaring the correlation coefficient (r2). It is a measure that indicates the proportion of the variance for a dependent variable that's explained by an independent variable in a regression model. An example provided in the reference information is that a correlation coefficient of -0.56 gives an r2 of approximately 0.31, meaning 31% of the variation in one variable is explained by the other.
Please remember that the coefficient of determination is always between 0 and 1. A value of 0 indicates no explanatory power, and a value of 1 indicates perfect explanatory power. It cannot be negative as it is a squared value.