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diamong [38]
3 years ago
9

Use the function m = 15f to find the value of m when f = 5. m =

Mathematics
2 answers:
elena55 [62]3 years ago
5 0

Answer:

\huge\boxed{Answer\hookleftarrow}

m = 15f

f = 5

✏ Substitute the value of f as 5 in the equation.

m = 15f \\ m = 15(5) \\ m = 15 \times 5 \\ m = 75

✏ The value of m is <u>7</u><u>5</u><u>.</u>

⋆┈┈。゚❃ུ۪❀ུ۪❁ུ۪❃ུ۪❀゚ུ۪。┈┈⋆

xeze [42]3 years ago
4 0

Answer:

  • m=15f
  • m=15×5
  • m=75

hope it helps

<h3>stay safe healthy and happy<u>.</u></h3>
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W3=24<br><br> w = 8<br><br> w = 72<br><br> w = 12<br><br> w = 6
antiseptic1488 [7]

Answer:

w=8

Step-by-step explanation:

W3=24

divide through by 3

therefore-

W=8

8 0
3 years ago
2) Juan had $622 in his checking account. He deposited a check for $180, and $100
adoni [48]

Answer:

867

Step-by-step explanation:

622+180+100=902

902-35=867

3 0
3 years ago
What is 6 1/3 yards in feet with explication
mojhsa [17]

Answer:

6 1/3 yards = 19 feet

Step-by-step explanation:

1 yard = 3 feet

So we'll take the number of yards and multiply that by 3

6 yards x 3 feet/yard = 18 feet

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Add up the parts, 18 + 1 = 19 feet

4 0
3 years ago
The executives of CareFree Insurance, Inc. feel that "a majority of our employees perceive a participatory management style at C
Mandarinka [93]

Answer:

Step-by-step explanation:

H_0: p = 0.5\\H_a : p >0.5

(One tailed test at 5% significance level)

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Std error of p = \sqrt{\frac{pq}{n} } \\=\sqrt{\frac{0.4(0.6)}{200} } \\=0.0346

Test statistic = p diff/std error = -2.89

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8 0
4 years ago
Find the indicated probability or percentage for the sampling error. The distribution of weekly salaries at a large company is r
Flauer [41]

Answer:

The probability that the sampling error made in estimating the mean weekly salary for all employees of the company by the mean of a random sample of weekly salaries of 80 employees will be at most $75 is 0.9297.

Step-by-step explanation:

According to the Central Limit Theorem if we have a non-normal population with mean <em>μ</em> and standard deviation <em>σ</em> and appropriately huge random samples (<em>n</em> > 30) are selected from the population with replacement, then the distribution of the sample means will be approximately normally distributed.

Then, the mean of the distribution of sample means is given by,

\mu_{\bar x}=\mu

And the standard deviation of the distribution of sample means is given by,

\sigma_{\bar x}=\frac{\sigma}{\sqrt{n}}

The information provided is:

\mu=\$1000\\\sigma=\$370\\n=80

As <em>n</em> = 80 > 30, the central limit theorem can be used to approximate the sampling distribution of sample mean weekly salaries.

Let \bar X represent the sample mean weekly salaries.

The distribution of \bar X is: \bar X\sim N(\$1000,\ \$41.37)

Now we need to compute the probability of the sampling error made in estimating the mean weekly salary to be at most $75.

The sampling error is the the difference between the estimated value of the parameter and the actual value of the parameter, i.e. in this case the sampling error is, |\bar X-\mu|= 75.

Compute the probability as follows:

P(-75

                                     =P(-1.81

Thus, the probability that the sampling error made in estimating the mean weekly salary for all employees of the company by the mean of a random sample of weekly salaries of 80 employees will be at most $75 is 0.9297.

3 0
3 years ago
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