here we are told that
number of dolls sold varies directly with advertising costs
number of dolls varies inversely with price of a doll
so initially
1800 dolls sold when advertising costs were $ 34 000
and price of a doll was $ 25
next they increased the advertising costs to $ 42 000
as we know number of dolls sold varies directly with advertising costs
so here when the advertising costs increase the number of dolls sold too should increases as its directly proportional relationship
we arent told that the price of a doll is changed so there's no effect on the number of dolls sold due to changes in price of a doll
only effect on number of dolls sold is due to increase in advertising costs
increase in advertising cost leads to increase in number of dolls sold
from the given options, only in one option the number of dolls sold are more than 1800 dolls. option is C with 2224 dolls
therefore correct answer is C. 2224 dolls
Answer:
it could maybe 50 or 525 hope this helps idrk
Step-by-step explanation:
<h3>
♫ - - - - - - - - - - - - - - - ~Hello There!~ - - - - - - - - - - - - - - - ♫</h3>
➷ Form an equation with 'x' as the unknown number
7x + 3 = -74
Subtract 3 from both sides:
7x = -77
Divide both sides by 7:
x = -11
The number is -11
<h3><u>
✽</u></h3>
➶ Hope This Helps You!
➶ Good Luck (:
➶ Have A Great Day ^-^
↬ ʜᴀɴɴᴀʜ ♡
Part A: The table does not represent y as a function of x. We can not input 1 and get 4 and 2 as outputs ( or input 3 and get 12 and 6 as outputs ).
Part B : f (120) is a cost for renting a peddleboat for 120 hours;
f (120) = 20 + 10 * 120 = 20 + 1,200 = 1,220.
Answer:
Standard error of mean = 689
Step-by-step explanation:
We are given the following information in the question:
Mean, μ = $28,520
Standard Deviation, σ = $5600
Mean of sampling distribution =
As per Central Limit Theorem, if the sample size is large enough, then the sampling distribution of the sample means follow approximately a normal distribution.
Sample size, n = 66
Since the sample size is large, we can use normal distribution for approximation.
Standard error of mean =
