Answer:
B
Step-by-step explanation:
according to pythagorean
(x>0)
=> 
=>
= 25
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Answers:
- (a) Independent
- (b) Dependent
- (c) Dependent
- (d) Independent
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Explanation:
If events A and B are independent, then the two following equations must both be true
- P(A | B) = P(A)
- P(B | A) = P(B)
This is because the conditional probability P(A|B) means "P(A) when B has happened". If B were to happen, then P(A) must be the same as before. In other words, event B does not affect A, and vice versa.
For part (a), we have P(B) = 1/4 and P(B|A) = 1/4 showing that P(B|A) = P(B) is true, and therefore we can say the events are independent. We don't need the info that P(A) = 1/8.
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Unlike part (a), part (b) has the answer "dependent" because P(A) = 1/8 and P(A | B) = 1/3 differ in value. Event A starts off at probability 1/8, but then event B occurring means P(A) gets increased to 1/3. The prior knowledge about B changes the chances of A. The P(B) = 1/5 is unneeded.
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If A and B were independent, then,
P(A and B) = P(A)*P(B)
However,
P(A)*P(B) = (1/4)*(1/5) = 1/20
which is not the same as P(A and B) = 1/6. Therefore the two events are dependent.
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Refer back to part (a)
P(A) = 1/4 and P(A|B) = 1/4 are identical in value, so P(A|B) = P(A) which leads to the events being independent. Whether we know event B happened or not, it does not affect the outcome of event A. P(B) = 1/9 is unneeded.
Answer:
graph C
Step-by-step explanation:
Well I lik it spread out cause you get more information and you can tell how the data is aligned and not scrunched up. Since the example said that the explanatory variable (indepdent variable) is best on the X axis, only C and A are left. A is all scrunch’s up and data could be read worng, but C is nice and spread and it shows all the data and rating clearly
