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Nadya [2.5K]
3 years ago
5

a team's stadium has a capacity of 86,047. The fan base is notorious for selling out of tickets every game. If every game sells

out this year, how many tickets are sold in their 12 game regular season play?
Mathematics
1 answer:
ycow [4]3 years ago
5 0

Answer:

1,032,564 tickets

Step-by-step explanation:

Find how many tickets they sell in total by multiplying the capacity of the stadium by the number of games in the season:

86,047(12)

= 1,032,564

So, if every game sells out, 1,032,564 tickets will be sold.

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To find the year when the two ad revenues were equal, we need to find the point of intersection of the two lines, which, from the graph, seems to be closest to 6 years ago (8 years on the chart).

4 0
3 years ago
It appears that people who are mildly obese are less active than leaner people. One study looked at the average number of minute
NemiM [27]

Answer:

a) 10.93% probability that the mean number of minutes of daily activity of the 5 mildly obese people exceeds 420 minutes.

b) 99.22% probability that the mean number of minutes of daily activity of the 5 lean people exceeds 420 minutes.

Step-by-step explanation:

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}}.

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.

Mildly obese

Normally distributed with mean 373 minutes and standard deviation 67 minutes. So \mu = 373, \sigma = 67

A) What is the probability that the mean number of minutes of daily activity of the 5 mildly obese people exceeds 420 minutes?

So n = 5, s = \frac{67}{\sqrt{5}} = 29.96

This probability is 1 subtracted by the pvalue of Z when X = 410.

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

Z = \frac{410 - 373}{29.96}

Z = 1.23

Z = 1.23 has a pvalue of 0.8907.

So there is a 1-0.8907 = 0.1093 = 10.93% probability that the mean number of minutes of daily activity of the 5 mildly obese people exceeds 420 minutes.

Lean

Normally distributed with mean 526 minutes and standard deviation 107 minutes. So \mu = 526, \sigma = 107

B) What is the probability that the mean number of minutes of daily activity of the 5 lean people exceeds 420 minutes?

So n = 5, s = \frac{107}{\sqrt{5}} = 47.86

This probability is 1 subtracted by the pvalue of Z when X = 410.

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

Z = \frac{410 - 526}{47.86}

Z = -2.42

Z = -2.42 has a pvalue of 0.0078.

So there is a 1-0.0078 = 0.9922 = 99.22% probability that the mean number of minutes of daily activity of the 5 lean people exceeds 420 minutes.

7 0
3 years ago
The distribution of the number of viewers for the American Idol television show follows a normal distribution with a mean of 26
hjlf

Answer:

Probability that next week's show will have between 30 and 37 million viewers is 0.2248.

Step-by-step explanation:

We are given that the distribution of the number of viewers for the American Idol television show follows a normal distribution with a mean of 26 million with a standard deviation of 8 million.

<em>Let X = number of viewers for the American Idol television show</em>

So, X ~ N(\mu=26,\sigma^{2}=8^{2})

Now, the z score probability distribution is given by;

          Z = \frac{X-\mu}{\sigma} ~ N(0,1)

where, \mu = population mean = 26 million

            \sigma = standard deviation = 8 million

So, probability that next week's show will have between 30 and 37 million viewers is given by = P(30 < X < 37) = P(X < 37) - P(X \leq 30)

    P(X < 37) = P( \frac{X-\mu}{\sigma} < \frac{37-26}{8} ) = P(Z < 1.38) = 0.91621

    P(X \leq 30) = P( \frac{X-\mu}{\sigma} \leq \frac{30-26}{8} ) = P(Z \leq 0.50) = 0.69146

<em>Therefore, P(30 < X < 37) = 0.91621 - 0.69146 = 0.2248</em>

Hence, probability that next week's show will have between 30 and 37 million viewers is 0.2248.

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