The linear equation to model the company's monthly expenses is y = 2.5x + 3650
<em><u>Solution:</u></em>
Let "x" be the units produced in a month
It costs ABC electronics company $2.50 per unit to produce a part used in a popular brand of desktop computers.
Cost per unit = $ 2.50
The company has monthly operating expenses of $350 for utilities and $3300 for salaries
We have to write the linear equation
The linear equation to model the company's monthly expenses in the form of:
y = mx + b
Cost per unit = $ 2.50
Monthly Expenses = $ 350 for utilities and $ 3300 for salaries
Let "y" be the total monthly expenses per month
Then,
Total expenses = Cost per unit(number of units) + Monthly Expenses
Thus the linear equation to model the company's monthly expenses is y = 2.5x + 3650
The answer would be
You got it right
I wish i saw this when i needed jt too
Explanation
Absolutely
A=30000+0.03S and B=25000+0.05S.
When A=B, 5000=0.02S, so S=$250000 when the earnings are the same.
The slope of A is smaller than that of B. In excess of this value of S B pays more than A and below it A pays more than B.
So answer option B. (When S=0, clearly A is better than B. Put S=$300000, A pays $39000 and B pays $40000).
The total of the running backs' salaries need to be added together first. So, $1 000 000 + $850 000 + $750 000 + $500 000 = $3 100 000. Now we divide the total number of salaries by the running back salaries: $3 100 000/$33 000 000 = 0.094 x 100 = 9.4 %.
Round off to nearest percent = 9.00 %.
Answer:
a) Calculate the probability that at least one of them suffers from arachnophobia.
x = number of students suffering from arachnophobia
= P(x ≥ 1)
= 1 - P(x = 0)
= 1 - [0.05⁰ x (1 - 0.05)¹¹⁻⁰
]
= 1 - (0.95)¹¹
= 0.4311999 = 0.4312
b) Calculate the probability that exactly 2 of them suffer from arachnophobia? 0.08666
= P(x = 2)
= (¹¹₂) x (0.05)² x (0.95)⁹
where ¹¹₂ = 11! / (2!9!) = (11 x 10) / (2 x 1) = 55
= 55 x 0.0025 x 0.630249409 = 0.086659293 = 0.0867
c) Calculate the probability that at most 1 of them suffers from arachnophobia?
P(x ≤ 1)
= P(x = 0) + P(x = 1)
= [(¹¹₀) x 0.05⁰ x 0.95¹¹] + [(¹¹₁) x 0.05¹ x 0.95¹⁰]
= (1 x 1 x 0.5688) + (11 x 0.05 x 0.598736939) = 0.5688 + 0.3293 = 0.8981
