Answer:
Step-by-step explanation:
Looking at the arrows on the graph, it appears that as the graph keep growing UP unbounded, it also keeps growing to the left unbounded (to negative infinity, to be exact). Looking to the right, it appears that as the graph decreases unbounded (the y values keep getting smaller), the graph keeps growing in the x direct to positive infinity. So the domain is
- ∞ < x < ∞
Answer:
0.0071 = 0.71% probability that the San Jose Sharks win 9 games in the upcoming month.
Step-by-step explanation:
For each game, there are only two possible outcomes. Either the Sharks win, or they do not. The probability of the Sharks winning a game is independent of any other game. This means that the binomial probability distribution is used to solve this question.
Binomial probability distribution
The binomial probability is the probability of exactly x successes on n repeated trials, and X can only have two outcomes.
In which is the number of different combinations of x objects from a set of n elements, given by the following formula.
And p is the probability of X happening.
The probability that the San Jose Sharks will win any given game is 0.3694.
This means that
An upcoming monthly schedule contains 12 games.
This means that
What is the probability that the San Jose Sharks win 9 games in the upcoming month?
0.0071 = 0.71% probability that the San Jose Sharks win 9 games in the upcoming month.
Answer:
a) probability that is cracked=1/30 (3.33%)
b) probability that is discoloured = 29/600 (4.83%)
c) probability that is cracked and discoloured = 11/600 (1.83%)
Step-by-step explanation:
assuming that each stone is equally likely to be chosen then defining the events C= the stone is cracked , D= the stone is discoloured , N= the stone is neither cracked or discoloured, then
P(C)= number of favourable outcomes/total number of outcomes = 20 stones/600 stones = 1/30 (3.33%)
P(D)= number of favourable outcomes/total number of outcomes = 29 stones/600 stones = 29/600 (4.83%)
the probability that is discoloured and cracked is P(C∩D) , where
P(C∪D)=P(C) + P(D)-P(C∩D)
and
P(C∪D)= 1- P(N)
thus
1- P(N)=P(C) + P(D)-P(C∩D)
P(C∩D)= P(N)+P(C)+P(D) -1
replacing values
P(C∩D)= P(N)+P(C)+P(D)=562/600 + 20/600 + 29/600 -1= 611/600 -1 = 11/600
thus
P(C∩D)= 11/600 (1.83%)
Answer:
The option in the top right...
Step-by-step explanation: