The following statistics represent weekly salaries at a construction company.
Mean $550. First quartile $480
Median $630 third quartile $700
Mode $605. 91st percentile $891
The most common salary is ?
The salary that half the employees salaries surpass is ?
The percent of employees salary that serve because $700 is ?
Percent of employees salaries that were less than $480 is
The percent of employees salaries this surpass $891 years
if the company has 104 is the total weekly salary of all employees he is $?

I don't know how to solve the questions

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Answer:

The most common salary is $605. The salary that half the employees salaries surpass is $630. The percent of employees salary that serve because $700 is 75%. Percent of employees salaries that were less than $480 is 25%. The 9% percent of employees salaries this surpass $891 years. The total weekly salary of 104 employees is 57200.

Step-by-step explanation:

It is given that mean is $550, first quartile is $480,  median is $630, third quartile is $700,  mode is $605 and 91st percentile is $891.

First quartile is at 25% of the data, median is at 50% of the data, third quartile is at 75% of the data.

The mode of a set of data values is the value that occurs most often.

The most common salary is mode, therefore the most common salary is $605.

The salary that half the employees salaries surpass is $630. Because median is the half of the data.

The percent of employees salary that serve because $700 is 75%. Because $700 is third quartile.

Percent of employees salaries that were less than $480 is 25%. Because $480 is first quartile.

The percent of employees salaries this surpass $891 years is 9%. Because $891 is 91 percentile. Therefore 9% employees get more than $891.

If the company has 104 employees than the total salary of employees is

[tex]104\times 550=57200[/tex]

because means is $550, therefore the total weekly salary of 104 employees is 57200.

The most common salary is [tex]605USD[/tex].

The salary that half the employees' salaries surpass is [tex]630USD[/tex].

The percent of employees salary that serves because [tex]700USD[/tex] is [tex]75[/tex]%.

The percent of employees' salaries that were less than [tex]480USD[/tex] is [tex]25[/tex]%.

The [tex]9[/tex]% percent of employees' salaries surpass [tex]891USD[/tex] years.

The total weekly salary of [tex]104[/tex] employees is [tex]57200[/tex].

Given Mean is [tex]550USD[/tex], the first quartile is [tex]480USD[/tex].

The Median is [tex]630USD[/tex], the third quartile is [tex]700USD[/tex], the Mode is [tex]605 USD[/tex] and the [tex]91st[/tex] percentile is [tex]891USD[/tex].

The first quartile is at [tex]25[/tex]% of the data, the median is at [tex]50[/tex]% of the data, the third quartile is at [tex]75[/tex]% of the data.

The mode of a set of data values is the value that occurs most often, So the most common salary is a mode, therefore the most common salary is [tex]605USD[/tex].

As the median is half of the data, the salary that half of the employees' salaries surpass is [tex]630USD[/tex].

Given that [tex]700USD[/tex]  is the third quartile, so the percent of employees ' salary that serves

The Percent of employees' salaries that were less than is % as  first quartile.

The percent of employees salaries this surpass $891 years is [tex]9[/tex] %. Because [tex]891USD[/tex] is [tex]91[/tex] percentile. Therefore more than [tex]891USD[/tex].

If the company has [tex]104[/tex] employees then the total salary of employees is

[tex]104\times550=57200[/tex] because means is [tex]550USD[/tex], therefore the total weekly salary of [tex]104[/tex] employees is [tex]57200 USD[/tex].

Therefore, the most common salary is [tex]605USD[/tex]. The salary that half the employees' salaries surpass is [tex]630USD[/tex]. The percent of employees salary that serves because [tex]700USD[/tex] is [tex]75[/tex]%. The percent of employees' salaries that were less than [tex]480USD[/tex] is [tex]25[/tex]%.The [tex]9[/tex]% percent of employees' salaries surpass [tex]891USD[/tex] years and the total weekly salary of [tex]104[/tex] employees is [tex]57200[/tex][tex]USD[/tex].

Know more about the statistical analysis here:

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