Question
What do you mean by linear and non linear correlation?
✓
Answer
Linear Correlation: Linear correlation said to exist when the ratio of change between X and Y is stable. In other words, when X and Y change in such a way that their ratio of change remains same throughout. It can be positive linear as will as negative linear correlation. In the given table, there is linear relation because throughout the ratio of change in X and change in Y is 1:2.
Non Linear Correlation: Non linear or curvi - linear correlation said to exist when the ratio of change between X and Y is not stable. In other words, when X and Y change in such a way that their ratio of change does not remain same throughout. It can be positive non linear as will as negative non linear correlation. In the given table, there is non linear relation because t the ratio of change in X and change in Y is not constant.
|
X
|
Y
|
|
1
|
10
|
|
2
|
8
|
|
3
|
6
|
|
4
|
4
|
|
5
|
2
|
|
X
|
Y
|
|
1
|
10
|
|
2
|
8
|
|
3
|
6
|
|
4
|
4
|
|
5
|
2
|
Non Linear Correlation: Non linear or curvi - linear correlation said to exist when the ratio of change between X and Y is not stable. In other words, when X and Y change in such a way that their ratio of change does not remain same throughout. It can be positive non linear as will as negative non linear correlation. In the given table, there is non linear relation because t the ratio of change in X and change in Y is not constant.
|
X
|
Y
|
|
1
|
20
|
|
2
|
17
|
|
3
|
12
|
|
4
|
8
|
|
5
|
3
|
|
X
|
Y
|
|
1
|
5
|
|
2
|
14
|
|
3
|
22
|
|
4
|
28
|
|
5
|
29
|
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