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Causes of water in a pie chart or bar chart?
Causes of Water in a pie chart should be shown because its easier to understand the causes of water problems in a pie charts rather than a bar graph b'coz studying a pie chart is easy b'coz the percentages of the information is given rather than studying numbers in a bar graph and now a days in the world when we make a projets where pie chart is included its very to study that information ( of that projet :p) .
Which control chart used for track the rejection in the maintenance project when the bug arrival pattern is not constant?
P Chart.
What is difference between power set and universal set?
From rule of set difference: A \ B = {x is element of A and not element of B} This is a little of first part of the question. When we have set A, set B and finding the difference of P(A) \ P(B) or the same as P(A) - P(B). First we have to make these two power sets of A, and of B. P(A) = { {}, subset of A, other subsets of A, , , (A its self)} P(B) = { {}, subset of B, other subsets of B, , , (B its self)} These two power sets will contain what ever subsets of A, or subsets of B, but first of their elements will be {}, which will be the same. From rule of set difference, I've seen many sample shown P(A) \ P(B) = { {}, subset of A, which not subset of B, , , } The big wonder is {}, the empty set still contained in the result set P(A) \ P(B), even though {} is contained in P(B). It did not being get rid off and other elements if they contained in P(B). Many internets show the same but never explain.
What is multiplication rule in probability?
Given two events, A and B, the conditional probability rule states that P(A and B) = P(A given that B has occurred)*P(B) If A and B are independent, then the occurrence (or not) of B makes no difference to the probability of A happening. So that P(A given that B has occurred) = P(A) and therefore, you get P(A and B) = P(A)*P(B)
What is the relationship between the probability of a simple event and its complement?
If the probability of an event is p, then the complementary probability is 1-p.
