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2 years ago

10

The work in a office takes 150 hours to complete every week. Each person in the office works for 32 hours a week. What is the sm

allest number of people needed to complete the work

1 answer:

nydimaria [60]2 years ago

6 0

In other words, how many times does 32 go into 150 without going over?

150/32 = 4.6875

Now, the smallest number of people needed to complete the work is found in the ones place or 4.

See it???

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Maggie wants to know how many students in her school enjoy watching sports on TV. She asks all 25 students in her math class and

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Determine+the+percentile+indicating+the+bottom+ranking+20%.+in+other+words,+what+is+the+dollar+number+that+defines+where+the+low

Aloiza [94]

The dollar number that defines where the lowest values falls is

20% percentile value =$20

This is further explained below.

<h3 /><h3>What is the dollar number that defines where the lowest value falls?</h3>

Generally, Now we need to determine the 20th percentile ($20). It indicates that we need to locate a dollar amount that marks the point at which the 20 % data has a value lower than that number.

i=(p/100)*n

Where i is the position of p^th

percentile when the data is presented in ascending order.

i=20/100*50

i=1000/100

i=10

Therefore

n=50

p=20

In conclusion, the 10th position for given data is 20,

Therefore, 20% percentile value =$20

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5 0

1 year ago

According to a study conducted in one city, 25% of adults in the city have credit card debts of more than $2000. A simple ran

Anvisha [2.4K]

Answer:

The sampling distribution of $\hat p$ is <em>N</em> (0.25, 0.0354²).

Step-by-step explanation:

According to the Central limit theorem, if from an unknown population large samples of sizes <em>n</em> > 30, are selected and the sample proportion for each sample is computed then the sampling distribution of sample proportion follows a Normal distribution.

The mean of this sampling distribution of sample proportion is:

$\mu_{\hat p}=p$

The standard deviation of this sampling distribution of sample proportion is:

$\sigma_{\hat p}=\sqrt{\frac{p(1-p)}{n}}$

Let <em>p</em> = proportion of adults in the city having credit card debts of more than $2000.

It is provided that the proportion of adults in the city having credit card debts of more than $2000 is, <em>p</em> = 0.25.

A random sample of size <em>n</em> = 150 is selected from the city.

Since <em>n</em> = 150 > 30 the Central limit theorem can be used to approximate the distribution of <em>p</em> by the Normal distribution.

The mean is:

$\mu_{\hat p}=p=0.25$

The standard deviation is:

$\sigma_{\hat p}=\sqrt{\frac{p(1-p)}{n}}=\sqrt{\frac{0.25(1-0.25)}{150}}=0.0354$

Thus, the sampling distribution of $\hat p$ is <em>N</em> (0.25, 0.0354²).

3 0

3 years ago