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3 years ago

1 Marlena has a bag of coins. The bag

Mathematics

1 answer:

poizon [28]3 years ago

8 0

Answer:

The probability is 1/6

Step-by-step explanation:

Firstly, we need to get the total number of coins

that would be the sum of all the coins present

We have this as;

8 + 10 + 4 + 2 = 24 coins

The number of nickels is 4

So the probability of selecting a nickel is the number of nickels divided by the total number of coins

We have this as;

4/24 = 1/6

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What is the domain of f(x)=5x^2 2x-1

adoni [48]

Domain of 5x^2 + 2x - 1 is all real numbers.

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3 years ago

If x = 7+3 root 5 by 7 - 3 root 5 , find the value of x^2 + 1 by x^2

Vesnalui [34]

Answer:

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Step-by-step explanation:

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2 years ago

Lim x approaches 0 (1+2x)3/sinx

jok3333 [9.3K]

Interpreting your expression as

$\dfrac{3(1+2x)}{\sin(x)}$

when $x$ approaches zero, the numerator approaches 3:

$3(1+2x) \to 3(1+2\cdot 0) = 3(1+0) = 3\cdot 1 = 3$

The denominator approaches 0, because $\sin(0)=0$

Moreover, we have

$\displaystyle \lim_{x\to 0^-} \sin(x) = 0^-,\quad \displaystyle \lim_{x\to 0^+} \sin(x) = 0^+$

So, the limit does not exist, because left and right limits are different:

$\displaystyle \lim_{x\to 0^-} \dfrac{3(1+2x)}{\sin(x)}= \dfrac{3}{0^-} = -\infty,\quad \displaystyle \lim_{x\to 0^+}\dfrac{3(1+2x)}{\sin(x)}= \dfrac{3}{0^+} = +\infty$

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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.