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zubka84 [21]
2 years ago
11

A set of face cards contains 4 Jacks, 4 Queens, and 4 Kings. Carlie chooses a card from the set, records the type of card, and t

hen replaces the card. She repeats this procedure a total of 60 times. Her results are shown in the table.
How does the experimental probability of choosing a Queen compare with the theoretical probability of choosing a Queen?

The experimental probability is 4 less than the theoretical probability.
The experimental probability is 1/15 less than the theoretical probability.
The experimental probability is 1/15 more than the theoretical probability.
The experimental probability is 4 more than the theoretical probability.

Mathematics
2 answers:
RUDIKE [14]2 years ago
8 0
The correct answer to this question is that "<span>The experimental probability is 1/15 less than the theoretical probability."

The table as attached via image shows that the probability of getting a Jack is 2/5, getting a Queen is 4/15, and King is 1/3. That is the theoretical probability of each card to be drawn according to its frequency.
</span>
maxonik [38]2 years ago
8 0

Answer:

the answer is b

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Determine the product of (46.2 × 10–1) ⋅ (5.7 × 10–6). Write your answer in scientific notation.
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b) = 5.7 x 10∧-6

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Rocky Mountain National Park is a popular park for outdoor recreation activities in Colorado. According to U.S. National Park Se
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Answer:

a) 0.6628 = 66.28% probability that at least 85 visitors had a recorded entry through the Beaver Meadows park entrance

b) 0.5141 = 51.41% probability that at least 80 but less than 90 visitors had a recorded entry through the Beaver Meadows park entrance

c) 0.5596 = 55.96% probability that fewer than 12 visitors had a recorded entry through the Grand Lake park entrance.

d) 0.9978 = 99.78% probability that more than 55 visitors have no recorded point of entry

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

E(X) = np

The standard deviation of the binomial distribution is:

\sqrt{V(X)} = \sqrt{np(1-p)}

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.

When we are approximating a binomial distribution to a normal one, we have that \mu = E(X), \sigma = \sqrt{V(X)}.

In this problem, we have that:

n = 175

(a) What is the probability that at least 85 visitors had a recorded entry through the Beaver Meadows park entrance?

46.7% of visitors to Rocky Mountain National Park in 2018 entered through the Beaver Meadows. This means that p = 0.467. So

\mu = E(X) = np = 175*0.467 = 81.725

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{175*0.467*0.533} = 6.6

This probability, using continuity correction, is P(X \geq 85 - 0.5) = P(X \geq 84.5), which is 1 subtracted by the pvalue of Z when X = 84.5. So

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

Z = \frac{84.5 - 81.725}{6.6}

Z = 0.42

Z = 0.42 has a pvalue of 0.6628.

66.28% probability that at least 85 visitors had a recorded entry through the Beaver Meadows park entrance.

(b) What is the probability that at least 80 but less than 90 visitors had a recorded entry through the Beaver Meadows park entrance?

Using continuity correction, this is P(80 - 0.5 \leq X <  90 - 0.5) = P(79.5 \leq X \leq 89.5), which is the pvalue of Z when X = 89.5 subtracted by the pvalue of Z when X = 79.5. So

X = 89.5

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

Z = \frac{89.5 - 81.725}{6.6}

Z = 1.18

Z = 1.18 has a pvalue of 0.8810.

X = 79.5

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

Z = \frac{79.5 - 81.725}{6.6}

Z = -0.34

Z = -0.34 has a pvalue of 0.3669.

0.8810 - 0.3669 = 0.5141

51.41% probability that at least 80 but less than 90 visitors had a recorded entry through the Beaver Meadows park entrance

(c) What is the probability that fewer than 12 visitors had a recorded entry through the Grand Lake park entrance?

6.3% of visitors entered through the Grand Lake park entrance, which means that p = 0.063

\mu = E(X) = np = 175*0.063 = 11.025

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{175*0.063*0.937} = 3.2141

This probability, using continuity correction, is P(X < 12 - 0.5) = P(X < 11.5), which is the pvalue of Z when X = 11.5. So

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

Z = \frac{11.5 - 11.025}{3.2141}

Z = 0.15

Z = 0.15 has a pvalue of 0.5596.

55.96% probability that fewer than 12 visitors had a recorded entry through the Grand Lake park entrance.

(d) What is the probability that more than 55 visitors have no recorded point of entry?

22.7% of visitors had no recorded point of entry to the park. This means that p = 0.227

\mu = E(X) = np = 175*0.227 = 39.725

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{175*0.227*0.773} = 5.54

Using continuity correction, this probability is P(X \leq 55 + 0.5) = P(X \leq 55.5), which is the pvalue of Z when X = 55.5. So

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

Z = \frac{55.5 - 39.725}{5.54}

Z = 2.85

Z = 2.85 has a pvalue of 0.9978

0.9978 = 99.78% probability that more than 55 visitors have no recorded point of entry

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