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3 years ago

Kate has a balance of $1,080 on her

Mathematics

2 answers:

mash [69]3 years ago

8 0

Answer:

yes

Step-by-step explanation:

12*90=1080 so yes

there are 12 months in a year and if she pays 90$ each month the equation will be 12*90=1080

vodomira [7]3 years ago

6 0

Answer:

Yes credit card balance be paid off in a year.

Step-by-step explanation:

12*90=1080 so yes , are 12 months in a year and if she pays 90$ each month the equation will be 12*90=1080

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The graph of the function f is shown. The domain of f is [0,50]. What is the range of g(x)=4f(x)?

sergij07 [2.7K]

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The range of $g(x)$ is $[0,7]$ .

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We must remember that range of function $f(x)$ corresponds to the set of values of $y$ in the graph (+y direction). Given that $g(x)$ is a stretched version of $f(x)$ , the range of $g(x)$ corresponds to the range of $f(x)$ multiplied by 4. Then,

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3 years ago

The number of surface flaws in plastic panels used in the interior of automobiles has a Poisson distribution with a mean of 0.08

kvv77 [185]

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:

$P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}$

In which

x is the number of sucesses

e = 2.71828 is the Euler number

$\mu$ 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.

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$

In which $C_{n,x}$ is the number of different combinations of x objects from a set of n elements, given by the following formula.

$C_{n,x} = \frac{n!}{x!(n-x)!}$

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 $\mu = 10*0.08 = 0.8$

(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).

$P(X = x) = \frac{e^{-\mu}*\mu^{x}}{(x)!}$

$P(X = 0) = \frac{e^{-0.8}*(0.8)^{0}}{(0)!} = 0.4493$

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 $p = 0.4493$ 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.