Answer:
(i) no correlation as one variable is not dependent on the other.
(ii) The age of a car does affects its value. Therefore, the age will be the independent variable (x-axis) and the value will be the dependent variable (y-axis). Unless the car is a classic, sought-after car, as the age increases, its value decreases, so this will be a negative correlation.
(iii) The time spent watching TV <u>may</u> affect exam score (since the more time spent watching TV equals less available time to spend studying). Therefore, the time spent watching TV will be the independent variable (x-axis) and the exam score will be the dependent variable (y-axis). As time spent watching TV increases, the exam score <u>could potentially</u> decrease, so this will be a negative correlation.
(iv) no correlation, since one variable is not dependent on the other.
(v) The cost of an apartment <u>may</u> affect its sale, but there are many factors that can affect this such as location of the apartment and the buyers it appeals to. The cost will be the independent variable (x-axis) and the sale will be the dependent variable (y-axis). In usual circumstances, we would expect to see as the cost of an apartment increases, the sale may decrease, as less and less buyers can afford to buy it, so this will be a negative correlation.
