linear model of the relationship between two quantitative variables in which the slope coefficient is non-zero.

#2
I believe C is the correct answer.

If the slope coefficient is positive, 1.2 for example, it is telling you there is a positive relationship between x and y, i.e. for every unit increase in x there is a 1.2 times unit increase in y.

If the slope coefficient is negative, -1.2 for example, it is telling you there is an inverse relationship between x and y, i.e. for every unit increase in x there is a 1.2 times unit decrease in y.

The correlation coefficient, r, is a measure of the relationship between two variables. It can range from -1 to 1. Values close to 1 indicated strong positive relationship whereas values close to -1 indicate a negative relationship, values around 0 suggest no evident relationship between the two variables. Therefore if you have a non-zero slope coefficient, it should be the same sign as the corresponding correlation coefficient.