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ivann1987 [24]
3 years ago
8

According to Masterfoods, the company that manufactures M&M’s, 12% of peanut M&M’s are brown, 15% are yellow, 12% are re

d, 23% are blue, 23% are orange and 15% are green. [Round your answers to three decimal places, for example: 0.123]
Mathematics
1 answer:
Oliga [24]3 years ago
8 0

Answer:

(a) P=0.850 (b) P=0.460 (c) P=0.053 (d) P=0.457 (e) P=0.543

Step-by-step explanation:

(a) Compute the probability that a randomly selected peanut M&M is not green.

P(X\neq G) = 1-P(X=G) = 1-0.15=0.850

(b)  Compute the probability that a randomly selected peanut M&M is blue or orange.

P(X=B or X=O) = P(X=B)+P(X=O) = 0.23+0.23 = 0.460

 

(c) Compute the probability that two randomly selected peanut M&M’s are both orange.

P(X1=O\& X2=O) = P(X=O)^2 = 0.23^2 = 0.053

(d) If you randomly select three peanut M&M’s, compute that probability that none of them are orange.

P(X1 \neq O \& X2\neq O \& X3\neq O) = (1-P(X=O)^3 = (1-0.23)^3 = 0.77^3 = 0.457

(e) If you randomly select three peanut M&M’s, compute that probability that at least one of them is orange.

We have to compute the probability that only one peanut is orange, plus the probaibility that only two peanuts are orange plus the probability that the three peanuts are orange

P(X1=O or X2=O or X3=O) = 3*P(X=O)*P(X≠O)^2 + 3*P(X=O)^2* P(X≠O)+P(X=O)^3\\\\P(X1=O or X2=O or X3=O)  =3*0.23*0.77^2+3*0.23^2*0.77+0.23^3\\\\P(X1=O or X2=O or X3=O)  = 0.409+0.122+0.012=0.543\\

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A quality control expert at LIFE batteries wants to test their new batteries. The design engineer claims they have a variance of
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Answer:

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Step-by-step explanation:

The main thing we have to take into account in this question is that we are about to find the probability of a <em>sample mean</em>. The distribution for <em>sample means</em> follows a <em>normal distribution</em> with mean \\ \mu and standard deviation \\ \frac{\sigma}{\sqrt{n}}. Mathematically

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The sample mean is \\ \overline{x} = 533.2

With all this information, we can solve the question

The probability that the mean battery life would be greater than 533.2 minutes

Using equation [1]

\\ z = \frac{\overline{x} - \mu}{\frac{\sigma}{\sqrt{n}}}

\\ z = \frac{533.2 - 530}{\frac{58}{\sqrt{75}}}

\\ z = \frac{3.2}{\frac{58}{8.66025}}

\\ z = \frac{3.2}{6.69726}

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With this value of z we can consult a <em>cumulative standard normal table</em> (or use some statistic program) to find the cumulative probability for <em>z</em> (and remember that this variable follows a standard normal distribution).

Most standard normal tables have values for z for only two decimals, so we can round the previous value for z as z = 0.48.

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\\ P(z

However, in the question we are asked for \\ P(z>0.48) = P(x>533.2). As well as all normal distributions, the standard normal distribution is symmetrical around the mean, and we have

\\ P(z>0.48) = 1 - P(z

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\\ P(z>0.48) = 1 - 0.68439

\\ P(z>0.48) = 0.31561

Rounding to four decimal places, we have

\\ P(z>0.48) = 0.3156

So, the probability that the mean battery life would be greater than 533.2 minutes is (in a sample of 75 batteries) \\ P(z>0.48) = P(x>533.2) = 0.3156.

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104 = 10,000 x 1.33 = 13,300

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