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3 years ago

2e=2 solve the question E=

Mathematics

2 answers:

lukranit [14]3 years ago

6 0

Answer: E=1

Step-by-step explanation:

because 2 times 1 is 2 or any number multiplied by 1 is itself

RideAnS [48]3 years ago

5 0

Answer:

e=1, e= -1

Step-by-step explanation:

Case 1:

2e=2

e=2/2

e=1

Case 2:

2e= -2

e= -2/2

e= -1

Hope this helped!!!

You might be interested in

Find the value of 7w-8 given that -4w-5=3<br> Simplify your answer as much as possible.<br> 7w - 8 =

blondinia [14]

Answer:

The value of 7w - 8 is -22

Step-by-step explanation:

Let us solve the question

∵ -4w - 5 = 3

→ Move -5 from the left side to the right side by adding both sides by 5

∴ -4w - 5 + 5 = 3 + 5

∴ -4w = 8

→ Divide both sides by -4

∵ $\frac{-4w}{-4}$ = $\frac{8}{-4}$

∴ w = -2

→ Now let us find the value of the given expression

∵ The given expression is 7w - 8

→ Substitute w by -2 to gets its value

∴ 7w - 8 = 7(-2) - 8

∴ 7w - 8 = -14 - 8

∴ 7w - 8 = -22

∴ The value of 7w - 8 is -22

8 0

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.