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Veronika [31]
3 years ago
8

Please help:) deadline is tonight :0 picture of question below

Mathematics
1 answer:
Nostrana [21]3 years ago
3 0
Annual growth rate is (1+0.15)^12. or 5.35025 or 535.025%
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Which box-and-whisker plot represents this data 5,8,4,2,5,9,7,12,4,3
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pag times mo po sya tyaka download ka photo ma tsaka ma kipag up a9e

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5. A man is 6 times as old as his daughter. The man's son is 4 years older than his sister.
maxonik [38]

Answer:

82-10=72

72:6=12 daughter`s age

12+4=16 son`s age

16+12= 28

72-28=44 man`s age

Step-by-step explanation:

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3 years ago
What is 68 x 15 - 8 + 22<br><br><br> Anyone wanna talk i'm bored
baherus [9]

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sorry but i'm in class right now

5 0
2 years ago
Read 2 more answers
a) A large hotel in Miami has 900 rooms (all rooms are equivalent). During Christmas, the hotel is usually fully booked. However
Olegator [25]

Answer:

14.69% probability that this happens

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

When the distribution is normal, we use 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.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

1000 people were given assurance of a room.

This means that n = 1000

Let us assume that each customer cancels their reservation with a probability of 0.1.

So 0.9 probability that they still keep their booking, which means that p = 0.9

Probability more than 900 still keeps their booking:

n = 1000, p = 0.9

So

\mu = 0.9, s = \sqrt{\frac{0.9*0.1}{1000}} = 0.0095

901/1000 = 0.91

So this is 1 subtracted by the pvalue of Z when X = 0.91.

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

By the Central Limit Theorem

Z = \frac{0.91 - 0.9}{0.0095}

Z = 1.05

Z = 1.05 has a pvalue of 0.8531

1 - 0.8531 = 0.1469

14.69% probability that this happens

3 0
3 years ago
Last year a video game cost $50. Price increase by 25% this year. What is the new price of this video game?
joja [24]
75.00$ dollars.......
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