Answer:
The answer to your question is:
Step-by-step explanation:
Factorize
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I need help with number 14
1 answer:
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Answer:
For the set X = {a, b, c}, the following three relations satisfy the required conditions in (a), (b) and (c) respectively.
(a) R = {(a,a), (b,b), (c, c), (a, b), (b, a), (b, c), (c, b)} is reflexive and symmetric but not transitive .
(b) R = {(a, a), (b, b), (c, c), (a, b)} is reflexive and transitive but not symmetric .
(c) R = {(a,a), (a, b), (b, a)} is symmetric and transitive but not reflexive .
Step-by-step explanation:
Before, we go on to check these relations for the desired properties, let us define what it means for a relation to be reflexive, symmetric or transitive.
Given a relation R on a set X,
R is said to be reflexive if for every .
R is said to be symmetric if for every .
R is said to be transitive if and
, then
.
(a) Let R = {(a,a), (b,b), (c, c), (a, b), (b, a), (b, c), (c, b)}.
Reflexive:
Therefore, R is reflexive.
Symmetric:
Therefore R is symmetric.
Transitive: but but (a,c) is not in R.
Therefore, R is not transitive.
Therefore, R is reflexive and symmetric but not transitive .
(b) R = {(a, a), (b, b), (c, c), (a, b)}
Reflexive:
Therefore, R is reflexive.
Symmetric:
Therefore R is not symmetric.
Transitive: and
.
Therefore, R is transitive.
Therefore, R is reflexive and transitive but not symmetric .
(c) R = {(a,a), (a, b), (b, a)}
Reflexive: but (b, b) and (c, c) are not in R
R must contain all ordered pairs of the form (x, x) for all x in R to be considered reflexive.
Therefore, R is not reflexive.
Symmetric: and
Therefore R is symmetric.
Transitive: and
.
Therefore, R is transitive.
Therefore, R is symmetric and transitive but not reflexive .
this question is incomplete, the complete question is:
1. is this model effective
2. what is the correlation coefficient for this data.
3. for a student with a bmi of 25, what is the predicted number of hours under the influence.
Step-by-step explanation:
1. first of all this model is not effective because we have r² as 0.134. this tells us that only 13.4 percent of the of the variations that exist in this data has been explained by the model
1. we get the correlation coefficient by
the regression slope coefficient has a negative sign. this is what we would use in calculating the correlation coefficient.
= -√0.134
= -0.366
therefore the correlation coefficient is -0.366
2. to get the number of hours under the influence with a bmi of 25
the equation is
49.2-1.15bmi
= 49.2-1.15(25)
= 49.2-28.75
= 20.45