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Lubov Fominskaja [6]
3 years ago
5

Cada caja contiene el mismo número de cuadernos. Si Mario transporta 120 cuadernos en total en una carretilla, ¿cuántos cuaderno

s habrá en 120 cajas iguales?
Mathematics
1 answer:
DIA [1.3K]3 years ago
3 0

Answer:

Se almacena un cuaderno por caja, significando 120 cuadernos en 120 cajas iguales.

Step-by-step explanation:

A partir del enunciado, podemos calcular el número de cuadernos por caja al dividir el total de cuadernos en la carretilla por el número de cajas disponibles.

x = \frac{120\,cuadernos}{120\,cajas}

x = 1\,\frac{cuadernos}{caja}

Se almacena un cuaderno por caja, significando 120 cuadernos en 120 cajas iguales.

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According to the MIT Airline Data Project, American Airlines controlled 15.5% of the domestic market during a recent year. A ran
andrey2020 [161]

Answer:

P(20

And we can use the z score given by:

z = \frac{x-\mu}{\sigma}

And if we find the z score for 20 and 25 we got:

z = \frac{20-19.375}{4.046}=0.154

z = \frac{25-19.375}{4.046}=1.390

And we have the probability given by:

P(20

And we can find this probbaility with this difference:

P(0.154< Z

Step-by-step explanation:

Previous concepts

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".

Let X the random variable of interest, on this case we now that:

X \sim Binom(n=125, p=0.155)

The probability mass function for the Binomial distribution is given as:

P(X)=(nCx)(p)^x (1-p)^{n-x}

Where (nCx) means combinatory and it's given by this formula:

nCx=\frac{n!}{(n-x)! x!}

We need to check the conditions in order to use the normal approximation.

np=125*0.155=19.375 \geq 10

n(1-p)=125*(1-0.155)=105.625 \geq 10

So we see that we satisfy the conditions and then we can apply the approximation.

If we appply the approximation the new mean and standard deviation are:

E(X)=np=125*0.155=19.375

\sigma=\sqrt{np(1-p)}=\sqrt{125*0.155(1-0.155)}=4.046

So then we can approximate the random variable like this:

X\sim N(\mu = 19.375 , \sigma=4.046)

And we are interested on this probability:

P(20

And we can use the z score given by:

z = \frac{x-\mu}{\sigma}

And if we find the z score for 20 and 25 we got:

z = \frac{20-19.375}{4.046}=0.154

z = \frac{25-19.375}{4.046}=1.390

And we have the probability given by:

P(20

And we can find this probbaility with this difference:

P(0.154< Z

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