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3 years ago

Si yo tengo una canasta llena de mangos y piñas, de las cuales hay 30

Mathematics

1 answer:

skelet666 [1.2K]3 years ago

7 0

Respuesta: Es más probable sacar un mango.

Explicación:

La probabilidad se refiere a la posibilidad de que un evento occura y no otro. En el caso que se describe, la probabilidad de sacar cada fruta puede ser calculada dividiendo el total de cada fruta en el número de frutas totales:

Probabilidad de sacar un mango:

$\frac{cantidad de mangos}{cantidad de frutas en la canasta}$ = $\frac{30}{50}$ = $0.6$

Probabilidad de sacar una piña:

$\frac{cantidad de pinas}{cantidad de frutas en la canasta} = \frac{20}{50}$ $= 0.4$

De acuerdo a lo anterior la probabilidad de sacar un mango es de 0.6 o de 60% (multiplica la probabilidad por 100 para saber su equivalente en porcentaje), mientras que la probabilidad de sacar un mango es de 0.4 o 40% lo cual es mucho más bajo. Es decir que es más probable sacar un mango.

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An orange juice producer buys oranges from a large orange grove that has one variety of orange. The amount of juice squeezed fro

skad [1K]

Answer:

The probability is 70% that the sample mean amount of juice will be contained between 4.9168 ounces and 5.0832 ounces.

Step-by-step explanation:

To solve this question, the Normal probability distribution and the Central Limit Theorem are important.

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , a large sample size can be approximated to a normal distribution with mean $\mu$ and standard deviation $\frac{\sigma}{\sqrt{n}}$

In this problem, we have that:

$\mu = 5, \sigma = 0.4, n = 25, s = \frac{0.4}{\sqrt{25}} = 0.08$

The probability is 70% that the sample mean amount of juice will be contained between what two values symmetrically distributed around the population mean?

The lower end of this interval is the value of X when Z has a pvalue of 0.5 - 0.7/2 = 0.15

The upper end of this interval is the value of X when Z has a pvalue of 0.5 + 0.7/2 = 0.85

Lower end

X when Z has a pvalue of 0.15. So X when $Z = -1.04$ .

$Z = \frac{X - \mu}{\sigma}$

Due to the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$-1.04 = \frac{X - 5}{0.08}$

$X - 5 = -1.04*0.08$

$X = 4.9168$

Upper end

X when Z has a pvalue of 0.15. So X when $Z = 1.04$ .

$Z = \frac{X - \mu}{\sigma}$

Due to the Central Limit Theorem

$Z = \frac{X - \mu}{s}$

$1.04 = \frac{X - 5}{0.08}$

$X - 5 = 1.04*0.08$

$X = 5.0832$

The probability is 70% that the sample mean amount of juice will be contained between 4.9168 ounces and 5.0832 ounces.

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3 years ago

Which of these expressions is a monomial?

Margarita [4]

A monomial has one term. Therefore, A is the only one with one term.

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3 years ago

Read 2 more answers

In a study of simulated juror decision making, Braden-Maguire, Sigal, and Perrino (2005) investigated the type of verdict assign

Licemer1 [7]

Answer:

Independence chi-square test

Step-by-step explanation:

The Chi-Square Test for independence is a type of statistical hypothesis test that is used to determine the existence of an association or relationship between nominal or categorical variables

The chi-square is given by the following formula;

$\chi^2 = \XXL\sum \dfrac{\left (O_i - E_i \right)^2}{E_i}$

The number of participants = 80

The number that assigned a verdict of guilty = 27

The number that assigned a verdict of not guilty by reason of self defense = 49

The number that assigned a verdict of not guilty by reason of insanity = 4

Independence Chi Square test

The table of values is presented as follows;

Expected Value = (Row sum * Column Sum)/(Grand Total)

Expected Value for Guilty = 27 × 80/80 = 27

Expected Value for Self Defense = 49 × 80/80 = 49

Expected value for Insanity = 4 × 80/80 = 4

$\begin{array}{ccc}Category&Observed&Expected\\Guilty&27&27\\SelfDe&49&49\\Insanity&4&4\end{array}$

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3 years ago

Consider the dot plot which shows the distribution of data collected on the amount of time Jason sleeps each night. Find the dif

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Answer:

A) 0.2

Step-by-step explanation:

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Dividing by 10, the mean is 72/10 = 7.2.

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3 years ago

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Answer:

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Step-by-step explanation:

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3 years ago