Suppose that a regression line for some data transformed with logarithms predicts that when x equals 6, log(y) will equal 2.012.
2 answers:
Answer: The regression line predicts that at x = 6, the value of y = 102.80.
Step-by-step explanation:
Since we have given that
When x = 6,
We need to find the value of 'y' when x=6:
Since it is logarithmic function with base 10.
So, it becomes,
Hence, The regression line predicts that at x = 6, the value of y = 102.80.
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Answer:
(1)Equivalence Relation
(2)Not Transitive, (0,3) is missing
(3)Equivalence Relation
(4)Not symmetric and Not Transitive, (2,1) is not in the set
Step-by-step explanation:
A set is said to be an equivalence relation if it satisfies the following conditions:
- Reflexivity: If
- Symmetry:
- Transitivity:
(1) {(0,0), (1,1), (2,2), (3,3)}
(3) {(0,0), (1,1), (1,2), (2,1), (2,2), (3,3)}
The relations in 1 and 3 are Reflexive, Symmetric and Transitive. Therefore (1) and (3) are equivalence relation.
(2) {(0,0), (0,2), (2,0), (2,2), (2,3), (3,2), (3,3)}
In (2), (0,2) and (2,3) are in the set but (0,3) is not in the set.
Therefore, It is not transitive.
As a result, the set (2) is not an equivalence relation.
(4) {(0,0), (0,1), (0,2), (1,0), (1,1), (1,2), (2,0), (2,2), (3,3)}
(1,2) is in the set but (2,1) is not in the set, therefore it is not symmetric
Also, (2,0) and (0,1) is in the set, but (2,1) is not, rendering the condition for transitivity invalid.