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const2013 [10]
2 years ago
5

Sally has just finished her thirty-fifth year with her company and is getting ready to retire. During her thirty-five years, Sal

ly’s average annual salary was $45,603. How much can Sally expect to receive from Social Security annually if she were to retire today? (Assume she will receive 42% of her average annual salary.)
Mathematics
2 answers:
Otrada [13]2 years ago
8 0
$19,153.26

If Sally got 42% of her aberage annual salary, that would be $45,603 * 42%.
olya-2409 [2.1K]2 years ago
7 0

The <em>correct answer</em> is:

$19,153.26.

Explanation:

She will receive 42% of her average annual salary. This salary was $45,603.

To find 42% of a number, we first convert the percent to a decimal: 42% = 42/100 = 0.42.

Next we multiply this by the number we're taking the percent of:

0.42(45603) = 19153.26.

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There are 8 sophomores on the academic team. At the last competition, they each took the math test. Their scores were 82%, 92%,
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Answer:

79%

Step-by-step explanation:

To find the median, you need to arrange the numbers in ascending order. Than pick the middle number. If there are two middle numbers then you add them together and then divide by 2.

3 0
2 years ago
Company F sells fabrics known as fat quarters, which are rectangles of fabric created by cutting a yard of fabric into four piec
jeka94

Answer:

a) Y 0 1 2

P(Y) 0.58 0.23 0.11

b) mean= 0.45, S.D= 0.6718

c) mean= 1.285, S.D= 8.74

Step-by-step explanation:

a) The following table shows the probability distribution of X:

X 0 1 2 3 4 or more

P(X) 0.58 0.23 0.11 0.05 0.03

Defect >2 = cannot be sold

Y = the number of defects on a fat quarter that can be sold by Company F.

Y = defect that can be sold

Y = Defect less or equal to 2 = 0,1,2

Probability distribution of the random variable Y:

Y 0 1 2

P(Y) 0.58 0.23 0.11

b) mean of Y (μ)

μ = Σ x*P(Y)

= (0*0.58) +(1*0.23)+(2*0.11)

= 0+0.23+0.22 = 0.45

Standard deviation of Y = σ

σ = Σ√(x-mean)^2*P(Y)

= Σ√[(x- μ )^2*P(Y)]

= √[(0-0.45)^2*0.58+ (1-0.45)^2*0.23 + (2-0.45)^2*0.11]

= √[0.11745 + 0.069575 +0.264275

= √(0.4513

σ = 0.6718

Company G:

σ for defect that be sold = 0.66

μ for defect that be sold = 0.40

Difference between μ of F and μ of G

= 0.45-0.40 = 0.05

Difference between σ of F and σ of G

= 0.67-0.66 = 0.01

Selling price of fat quarter without defect = $5

Discount per defect = $1.5

Selling price per defect = 5-1.5 = $3.5

Discount per 2 defect = $1.5*2 = $3

Selling price per defect = 5-3 = $2

Since defect to be sold cannot be greater than 2, let Y = 5,3,2

Probability distribution of the selling price Y:

Y 5 3 2

P(Y) 0.58 0.23 0.11

μ = (5*0.58) +(3.5*0.23)+(2*0.11)

μ = 2.9+0.805+0.22 =1.285

σ = Σ√[(x- μ )^2*P(Y)]

σ = √[(5-1.285)^2*0.58+ (3-1.285)^2*0.23 + (2-1.285)^2*0.11]

σ = 8.00+0.68+0.06 = 8.74

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