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ziro4ka [17]
2 years ago
8

40 tickets were sold for a concert, some at 75 cents and the rest at $1.25. if the total raised was $42, how many had the cheape

r ticket. please i need this for an assignment​
Mathematics
1 answer:
Murljashka [212]2 years ago
3 0

Answer:

34

Step-by-step explanation:

$1.25 = 125 cents.

$42 = 4200 cents

Tickets sold at 75 cents = x

Tickets sold at 125 cents = y

x + y = 40

75x + 125y = 4200

Multiply the first equation by 75

75x + 75y = 3000

75x + 125y = 4200

Subtract the the second equation from the first.

75x + 75y = 3000

- 75x + 125y = 4200

-------------------------------

0 - 150y = - 1200

Divide both sides by - 150

-150y/-150 = -1200/-150

y = 8

Substitute y = 8 into the first equation

x + y = 42

x + 8 = 42

x = 42 - 8

x = 34

34 tickets were sold for 75 cents

8 tickets were sold for $1.25

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0.1324 = 13.24% probability that no less than 96 out of 145 people will not get the flu this winter.

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:

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The standard deviation of the binomial distribution is:

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Normal probability distribution

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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 = 145, p = 0.61

So

\mu = E(X) = np = 145*0.61 = 88.45

\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{145*0.61*0.39} = 5.87

Consider the probability that no less than 96 out of 145 people will not get the flu this winter.

More than 95 people, which is the same as 1 subtracted by the pvalue of Z when X = 95. So

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

Z = \frac{95 - 88.45}{5.87}

Z = 1.115

Z = 1.115 has a pvalue of 0.8676

1 - 0.8676 = 0.1324

0.1324 = 13.24% probability that no less than 96 out of 145 people will not get the flu this winter.

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