Sqrt(3x)-1=-4 1.)x=3 2.)x=-3 3.) no solution 4.)x= 25/3

A diagram shows a kite and its frame.

kati45 [8]

Answer:

indeed it does

Step-by-step explanation:

wheres the diagram exactly?

7 0

3 years ago

A rectangle has dimensions 5 and one fourth

Mariulka [41]

The area of one triangle is 28.875 inches.

8 0

3 years ago

Divide 7 by 10 the write answer as a fraction

mash [69]

1/7

Step-by-step explanation:

3 0

3 years ago

Read 2 more answers

An automobile manufacturer finds that 1 in every 2500 automobiles produced has a particular manufacturing defect. (a) Use a bin

Advocard [28]

Answer:

a) 0.1558 = 15.58% probability of finding 4 cars with the defect in a random sample of 7000 cars.

b) 0.1557 = 15.57% probability of finding 4 cars with the defect in a random sample of 7000 cars. These probabilities are very close, which means that the approximation works.

Step-by-step explanation:

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:

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.

To use the Poisson approximation for the binomial, we have that:

$\mu = np$

1 in every 2500 automobiles produced has a particular manufacturing defect.

This means that $p = \frac{1}{2500} = 0.0004$

a) Use a binomial distribution to find the probability of finding 4 cars with the defect in a random sample of 7000 cars.

This is $P(X = 4)$ when $n = 7000$ . So

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

$P(X = 4) = C_{7000,4}.(0.0004)^{4}.(0.9996)^{6996} = 0.1558$

0.1558 = 15.58% probability of finding 4 cars with the defect in a random sample of 7000 cars.

(b) The Poisson distribution can be used to approximate the binomial distribution for large values of n and small values of p.

Using the approximation:

$\mu = np = 7000*0.0004 = 2.8$ . So

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

$P(X = 4) = \frac{e^{-2.8}*(2.8)^{4}}{(4)!} = 0.1557$

0.1557 = 15.57% probability of finding 4 cars with the defect in a random sample of 7000 cars. These probabilities are very close, which means that the approximation works.

6 0

3 years ago

A chance event with probability 1 is certain to happen.

motikmotik

Answer:

True, for Probability of a chance event certain to happen is 1.

Step-by-step explanation:

Given that,

A chance of event with probability of happening certainly is 1.

To find:- Is it true or false?

from the given scenario,

Probability states that P(Event) is a number describing the chance of that event will happen And value of $P(E)$ lies between $0\leq P(E)\leq 1$ ..

$P(An Event) =$ $\frac{Number of favourable outcomes}{Total number of outcomes}$

When An Event is certain to occur then its $P(E) = 1$ .

when An Event cannot possible to occur then its $P(E) = 0$ .

And

Is there any chance that event will occur then its value lies $0\leq P(E)\leq 1$ .

Let us take an Example:-

If it is Saturday, then the probability that tomorrow is Sunday is certain, therefore the probability is 1.
The probability that tomorrow is Friday if today is Sunday is 0.

Hence,

True, for Probability of a chance event certain to happen is 1.

3 0

4 years ago