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olya-2409
13 days ago
13

A mechanical dart thrower throws darts independently each time, with probability 10% of hitting the bullseye in each attempt. Th

e chance that the dart thrower hits the bullseye at least once in 6 attempts is:
Mathematics
1 answer:
lawyer [12.1K]13 days ago
3 0

Answer:

The likelihood of achieving the bullseye at least one time in 6 attempts is 0.469.

Step-by-step explanation:

It's stated that a mechanical dart thrower independently releases darts with a 10% probability of hitting the bullseye for each throw.

The chance of hitting the bullseye in a single throw, p = 0.10

The probability of failing to hit the bullseye on each throw, q = 1-p = 1-0.10 = 0.90

Let x represent the event of hitting the bullseye.

Our goal is to determine the probability of striking the bullseye at least once in 6 throws.

P(x\geq 1)=1-P(x=0).... (1)

According to the binomial formula

P(x=r)=^nC_rp^rq^{n-r}

where n refers to total attempts, r is the success count, p is the probability of success, and q denotes the failure probability.

The probability that the dart thrower fails to hit the bullseye in 6 attempts is

P(x=0)=^6C_0(0.10)^0(0.90)^{6-0}

P(x=0)=0.531441

Substituting the value of P(x=0) in (1).

P(x\geq 1)=1-0.531441

P(x\geq 1)=0.468559

P(x\geq 1)\approx 0.469

Thus, the probability of hitting the bullseye at least once across 6 attempts is 0.469.

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Suppose that the weights of airline passenger bags are normally distributed with a mean of 47.88 pounds and a standard deviation
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Answer:

There is a probability of 24.51% that the weight of a bag exceeds the maximum permitted weight of 50 pounds.

Step-by-step explanation:

Problems dealing with normally distributed samples can be addressed using the z-score formula.

For a set with the mean \mu and a standard deviation \sigma, the z-score for a measure X is calculated by

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

Once the Z-score is determined, we consult the z-score table to find the related p-value for this score. The p-value signifies the likelihood that the measured value is less than X. Since all probabilities total 1, calculating 1 minus the p-value gives us the probability that the measure exceeds X.

For this case

Imagine the weights of passenger bags are normally distributed with a mean of 47.88 pounds and a standard deviation of 3.09 pounds, thus \mu = 47.88, \sigma = 3.09

What probability exists that a bag’s weight will surpass the maximum allowable of 50 pounds?

That translates to P(X > 50)

Thus

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

Z = \frac{50 - 47.88}{3.09}

Z = 0.69

Z = 0.69 has a p-value of 0.7549.

<pthis indicates="" that="" src="https://tex.z-dn.net/?f=P%28X%20%5Cleq%2050%29%20%3D%200.7549" id="TexFormula10" title="P(X \leq 50) = 0.7549" alt="P(X \leq 50) = 0.7549" align="absmiddle" class="latex-formula">.

Additionally, we have that

P(X \leq 50) + P(X > 50) = 1

P(X > 50) = 1 - 0.7549 = 0.2451

There is a probability of 24.51% that the weight of a bag will exceed the maximum allowable weight of 50 pounds.

</pthis>
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