At Sports Shoe Warehouse, the cost of 11 pairs of soccer shoes is $1100 plus $66 for each additional pair. From Winning Team Shoes, the cost of 11 pairs of soccer shoes is $825 plus an additional 6% for each additional pair. For how many total pairs of soccer shoes does each vendor cost about the same? Write the equations

The cost of the stores will be the same when "-6" pair of shoes are bought, therefore they will never be the same in real world applications.

Step-by-step explanation:

In order to solve this problem we will create equations for each store, where "s" is the total number of shoe pairs that were bought.

For the store A:

total cost = 1100 + 66*(s - 11)

total cost = 1100 + 66*s -726

total cost = 374 + 66*s

For the store B:

total cost = 825 + 825*0.06*(s-11)

total cost = 825 + 49.5(s -11)

total cost = 825 + 49.5*s -544.5

total cost = 49.5*s +280.5

In order for the cost to be the same, the expressions must be equal, therefore:

374 + 66*s = 49.5*s +280.5

66*s - 49.5*s = 280.5 - 374

15.5*s = -93.5

s = -6.03

Since the value for pair of shoes is negative, this means that the cost for each vendors will never be the same.

answer is d-29

step-by-step explanation:

since you didn't include the picture, i can give you the description so you know how to pick the correct answer. the third quartile of a data is always shown in a box plot. in the middle of your graph should be a box. the third quartile is the value that goes with the far right edge of the box.

part a

answer: a reasonable domain is where n is a real number. so n can be between 0 and 10. both endpoints are included.

work shown:

n is the number of days after the experiment starts. the smallest n can be is n = 0 which means that 0 days have gone by, and we're at the start. to find out how large n should be, then replace f(n) with 16.13 and solve for n. use logarithms to isolate the exponent.

f(n) = 12*(1.03)^n

16.13 = 12*(1.03)^n

16.13/12 = (1.03)^n

1.34416666666667 = (1.03)^n

(1.03)^n = 1.34416666666667

log[ (1.03)^n ] = log[ 1.34416666666667 ]

n*log[ 1.03 ] = log[ 1.34416666666667 ]

n = log[ 1.34416666666667 ]/log[ 1.03 ]

n = 10.0062999823929

this rounds to n = 10 which is fairly close but not 100% perfect. so this is the largest n can be.

note: if you plug n = 10 into f(n), you'll get roughly 16.127 which rounds to 16.13 (this comes up again in part c)

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part b

answer: the y intercept is 12. it represents the starting height of the plant in cm.

work shown:

plug n = 0 into the f(n) function. simplify

f(n) = 12*(1.03)^n

f(0) = 12*(1.03)^0

f(0) = 12*(1)

f(0) = 12

on day n = 0, aka the starting point, the height f(n) is 12 cm

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part c

answer: the average rate of change is approximately 0.43061036458991 (round however you need to). this represents the average growth rate from day n = 3 to day n = 10. so the plant grew roughly 0.43 cm per day during this timespan, assuming you round to 2 decimal places.

work shown:

compute f(3)

f(n) = 12*(1.03)^n

f(3) = 12*(1.03)^3

f(3) = 13.112724 < we'll use this later

compute f(10)

f(n) = 12*(1.03)^n

f(10) = 12*(1.03)^10

f(10) = 16.1269965521294 < we'll use this later

now use the formula below with a = 3 and b = 10

aroc = average rate of change

aroc = [ f(b) - f(a) ]/[ b - a ]

aroc = [ f(10) - f(3) ]/[ 10 - 3 ]

aroc = (16.1269965521294 - 13.112724)/(10 - 3)

aroc = 3.0142725521294/7

aroc = 0.43061036458991

round this however you need to

note: the plant grew approximately 3.01 cm over 7 days, so roughly 0.43 cm per day is the average growth rate (if you were to round to 2 decimal places).