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please finish these questions after watching the videos please
1.Which of the following was offered as an example of continuous sample space?
Group of answer choices
amazon ratings
zip codes
blood types
cholesterol levels
2.In probability, which represents the union of the event A and the event B?
P(A or B)
P(A | B)
P(B | A)
P(sample space)
P(A and B)
3. In probability, which represents the intersection of the event A and the event B?
4.The rule of the complement, for some random event E, is that
P(E) = 1 – P(not E)
P(E) = P(not E)
P(E) = 1 / P(not E)
P(not E) does not equal P(E)
5. In the box of chocolates example in which you eat the first chocolate you pick, the successive chocolate picks are
randomized.
independent.
related.
dependent.
unrelated
6. In the pool example, we concluded that events DF and IC are dependent events because
IC causes pool filters to get dirty faster.
we found that P(IC | DF) was different from P(IC).
a pool can have both IC and DF.
a pool can have DF and not have IC.
8.The confusion of the inverse is:
confusing P(A) with P(not A)
confusing P(A | B) with P(B | A)
confusing P(A or B) with P(A and B)
confusing P(A) with P(B | A)
9.If “6ft+” stands for a human height of at least 6 feet, then P(6ft+ | man) is the probability
of being a man but not one who is 6ft+ tall.
of being a man if the person is 6ft+ tall.
of being 6ft+ tall but not a man.
of being neither a man nor 6ft+ tall.
of being a man and being 6ft+ tall.
of being 6ft+ tall if the person is a man.
10. If “6ft+” stands for a human height of at least 6 feet, then we can see from the distribution of adult heights shown in the videos that
P(man | 6ft+) = 1 – P(6ft+ | man)
P(man | 6ft+) < P(6ft+ | man)
P(man | 6ft+) > P(6ft+ | man)
P(man | 6ft+) = P(6ft+ | man)
13.In probability, a traditional two-way table displays what inside the inner cells of the table?
conditional probabilities
joint probabilities
inverse probabilities
marginal probabilities
14. In probability, the rectangles making up a mosaic diagram are scaled to represent
marginal probabilities.
inverse probabilities.
conditional probabilities.
joint probabilities.
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