needing definitions
1. Negative vs positive association
2. No association
3. Linear vs Nonlinear relationship
1. Negative vs positive association:
Negative association refers to a relationship between two variables where an increase in one variable is typically associated with a decrease in the other variable. In other words, as one variable increases, the other variable tends to decrease. Positive association, on the other hand, refers to a relationship between two variables where an increase in one variable is typically associated with an increase in the other variable. In this case, as one variable increases, the other variable also tends to increase.
2. No association:
No association refers to a lack of relationship or correlation between two variables. This means that changes in one variable do not affect or have any relationship with changes in the other variable. In other words, the variables are independent of each other and there is no pattern or trend between them.
3. Linear vs Nonlinear relationship:
A linear relationship refers to a relationship between two variables where the relationship can be represented by a straight line on a graph. In this case, as one variable increases or decreases, the other variable changes proportionally in a consistent manner. A nonlinear relationship, on the other hand, refers to a relationship between two variables where the relationship cannot be represented by a straight line. The relationship may follow a curve or have varying degrees of change between the variables.