By maximizing the amount of cheaper nuts and minimizing the amount of expensive nuts, the manufacturer should use a mix of 50% peanuts, 40% cashews, and 10% almonds. The profit per can will be $1.87, closest to $1.77 out of the given choices.
This problem involves linear programming, and it is a problem of maximizing profit under given constraints. The proportions of nuts can be found using optimization techniques that are usually covered in calculus or advanced algebra classes, but a quick answer can be given here by considering the cost of each type of nut.
The manufacturer should maximize the amount of the cheapest nuts in the mix to increase the profit. So, they should fill the can with 50% peanuts ($0.55 per lb), 40% cashews ($1.20 per lb), and 10% almonds ($2.75 per lb) to meet the minimum requirement for almonds and maximum constraints for peanuts and cashews. The average cost of this mix per pound will be (0.5x0.55)+(0.4x1.2)+(0.1x2.75) which equals $1.025 per lb. If the can costs $0.10, the total manufacturing cost per can becomes $1.125.
If the nut mix is sold at $3.00, the profit per can will be $3.00 - $1.125 which equals $1.87. This is closer to $1.77. Therefore, the answer should be $1.77 if we consider rounding to the closest number. Note that we can't fill a full can because the total proportion is already 100%, but we have ignored the volume taken up by the can itself in this calculation.
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Answer:
Nut
Step-by-step explanation:
moltiplicacion
x
50
250
+
X
50
11
Soo
-
X
50
Answer:
I’ll neve switch on u dxxdy
Step-by-step explanation:
image attached
Step-by-step explanation:
this is only asking about the functional values.
in what intervals are the functional values going up (when increasing x from left to right), and in what intervals is the functional value going down (again, when increasing x from left to right) ?
and so we see in the graph,
it is increasing (y-values are going up) in
(-infinity, -1], (2, +infinity)
it is decreasing (y- values are going down) in
(-1, 2]
please consider the used types of brackets.
"(", ")" means the corresponding interval end is NOT included.
"[", "]" mags the corresponding interval end is included.
"infinity" is only a concept and not a value, so it can never be included.
and I wanted the intervals to have no overlap. so, I included "-1" in one and excluded it in the connecting interval. the same for "2".
but if your teacher prefers to have the interval ends overlapping, then please change these brackets to "["as needed. it all depends on what your teacher defined for you.
Answer:
27
Step-by-step explanation:
First is 9 / 3 which is 3 and then 4 x 6 which is 24 then 24 + 3 = 27
Answer:
PEMDAS
4 × 6 is 24
9 ÷ 3 is 3
24 + 3 = 27
Step-by-step explanation:
Answer:
15 cos(33°) m
Step-by-step explanation
Presumably m stands for meters.
If RS were 1, x would be cos(33°)
Multiply sides of triangle by 15 m
When calculating cos(33°) first make sure cos(90°) comes out zero, not -0.448...
Answer:
Step-by-step explanation:
to the nearest whole number, we take a note of the number after the decimal point
any number higher than 5, 1 is added
but in these case, it is less than 5
835.2301≅835
Answer:
Sample size should be atleast 625
Step-by-step explanation:
Given that the Labor Bureau wants to estimate, at a 90% confidence level, the proportion of all households that receive welfare
Sample proportion = 17.5%
Let n be the sample size
Standard error of sample proportion=
Z critical for 90% = 1.645
Margin of error = 1.645 * std error
Since margin of error<0.025 we have
The sample size that would limit the margin of error to be within 0.025 of the population proportion is approximately 185.
To estimate the sample size needed to limit the margin of error within 0.025, we can use the formula for sample size in proportion estimation. The formula is:
n = (Z^2 * p * (1-p)) / (E^2)
Where:
n = sample size
Z = Z-score corresponding to the desired confidence level
p = preliminary sample proportion
E = margin of error
Given that the confidence level is 90%, the Z-score for a 90% confidence level is approximately 1.645. The preliminary sample proportion is 17.5% (or 0.175) and the margin of error is 0.025.
Substituting these values into the formula:
n = (1.645^2 * 0.175 * (1 - 0.175)) / (0.025^2)
Simplifying the equation:
n = 1.645^2 * 0.175 * 0.825 / 0.025^2
n ≈ 185.16
So, the sample size that would limit the margin of error to be within 0.025 of the population proportion is approximately 185, rounded up to the nearest whole number.
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