Which viewing window boundaries would allow you to see all the intercepts and the maximum, as closely as possible, for the funct
ion y = –x2 + 3x + 20?
The minimum window boundary for the x-axis should be
The maximum window boundary for the x-axis should be
The minimum window boundary for the y-axis should be
The maximum window boundary for the y-axis should be
The minimum window boundary for the x-axis should be
The maximum window boundary for the x-axis should be
The minimum window boundary for the y-axis should be
The maximum window boundary for the y-axis should be
2 answers:
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Answer:
a) 44.93% probability that there are no surface flaws in an auto's interior
b) 0.03% probability that none of the 10 cars has any surface flaws
c) 0.44% probability that at most 1 car has any surface flaws
Step-by-step explanation:
To solve this question, we need to understand the Poisson and the binomial probability distributions.
Poisson distribution:
In a Poisson distribution, the probability that X represents the number of successes of a random variable is given by the following formula:
In which
x is the number of sucesses
e = 2.71828 is the Euler number
is the mean in the given interval.
Binomial 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.
Poisson distribution with a mean of 0.08 flaws per square foot of plastic panel. Assume an automobile interior contains 10 square feet of plastic panel.
So
(a) What is the probability that there are no surface flaws in an auto's interior?
Single car, so Poisson distribution. This is P(X = 0).
44.93% probability that there are no surface flaws in an auto's interior
(b) If 10 cars are sold to a rental company, what is the probability that none of the 10 cars has any surface flaws?
For each car, there is a probability of having no surface flaws. 10 cars, so n = 10. This is P(X = 10), binomial, since there are multiple cars and each of them has the same probability of not having a surface defect.
0.03% probability that none of the 10 cars has any surface flaws
(c) If 10 cars are sold to a rental company, what is the probability that at most 1 car has any surface flaws?
At least 9 cars without surface flaws. So
0.44% probability that at most 1 car has any surface flaws