Final answer:
The regression results indicate a significant linear relationship between x and y, with a correlation coefficient significantly different from zero showing that changes in x can predict changes in y.
Step-by-step explanation:
The regression results suggest that there is a significant linear relationship between the two variables, x and y. When the correlation coefficient is significantly different from zero, it implies that as one variable changes, the other variable tends to change in a specific direction (either positively or negatively associated). The relationship is further supported if a scatter plot of the data shows a linear trend. This linear association means that the regression line, represented by the equation î = a + bx, can reliably be used as a model to predict the value of y based on the value of x.
Furthermore, the strength of the relationship is indicated by the number portion of the correlation coefficient. A number close to 1 or -1 signifies a strong relationship where changes in one variable are closely related to changes in the other. Conversely, a number close to zero indicates a weak relationship.