Help with this please

*<br> Unions are important in today's economy because they

DedPeter [7]

Step-by-step explanation:

Unions are important because they help set the standards for education, skill levels, wages, working conditions, and quality of life for workers. Union-negotiated wages and benefits are generally superior to what non-union workers receive. Most union contracts provide far more protections than state and federal laws.

7 0

3 years ago

Robyn had 8 apples. She ate3/8 of them. What is the number of apples she ate?

Leni [432]

Since she only has 8 apples and she ate 3 of 8, she ate 3 apples.

8 0

3 years ago

Read 2 more answers

What is 3.2 m converted to centimeters?

SOVA2 [1]

3.2 m is converted to 320 cm

3 0

3 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

What is the equation for exponential growth in Biology?

SpyIntel [72]

The exponential growth in biology is A=Pert, where "A" is the ending amount of whatever you're dealing with , "P" is the beginning amount of that same "whatever", "r" is the growth or decay rate, and "t" is time. The formula is related to the compound-interest formula, and represents the case of the interest being "compounded continuously".

8 0

3 years ago