What can be inferred about the slope of a regression line if the correlation between years of experience and salary is positive?

When the correlation between years of experience and salary is positive, it indicates that as one variable (years of experience) increases, the other variable (salary) also tends to increase. In regression analysis, the slope of the regression line quantifies this relationship between the independent variable (in this case, years of experience) and the dependent variable (salary).

A positive correlation implies that the slope of the regression line will also be positive. This means that for every additional year of experience, the salary is expected to increase by a certain amount, represented by the slope. This relationship illustrates a direct and positive trend between the two variables.

In contrast, a negative slope would indicate that an increase in years of experience would correspond with a decrease in salary, which conflicts with the notion of a positive correlation. A zero slope would suggest that there is no relationship between the two variables, meaning changes in experience do not affect salary, which is also not in line with a positive correlation. Likewise, stating that there is no slope altogether would imply a lack of relationship, again inconsistent with the positive correlation identified.

Therefore, the conclusion that the slope of the regression line is positive aligns well with the positive correlation observed between years of experience and salary.