Answer:
a. 61.92 in²
b. 21.396 ≈ 21.4%
c. $4.71
Step-by-step explanation:
a. Amount of waste = area of rectangular piece of stock - area of two identical circles cut out
Area of rectangular piece of stock = 24 in × 12 in = 288 in²
Area of the two circles = 2(πr²)
Use 3.14 as π
radius = ½*12 = 6
Area of two circles = 2(3.14*6²) = 226.08 in²
Amount of waste = 288 - 226.08 = 61.92 in²
b. % of the original stock wasted = amount of waste ÷ original stock × 100
= 61.92/288 × 100 = 6,162/288 = 21.396 ≈ 21.4%
c. 288 in² of the piece of stock costs $12.00,
Each cut-out circle of 113.04 in² (226.08/2) will cost = (12*113.04)/288
= 1,356.48/288 = $4.71.
<u>Answer:</u>
The correct answer option is B. 2 = 3x + 10x^2
<u>Step-by-step explanation:</u>
We are to determine whether which of the given equations in the answer options can be solved using the following expression:
Here, 
and 
.
These requirements are fulfilled by the equation 4 which is:
Rearranging it to get:
Substituting these values of 
in the quadratic formula:
You're nearly there. Just some more steps.
557 * x = 594 tells us
x = 594 / 557 (divide both sides by 557)
x ≈ 1.066427
When we've found this number we must realise the following:
the '1' in this answer is the 100% the car fixing costs (without taxes)
the '0.66427' stands for the tax rate.
To find the tax rate we multiply 0.66427 by 100, which gives us:
0.66427 * 100 = 6.6427 ≈ 7
So, rounded to the nearest %, the tax rate is 7%
Answer:
I don’t have enough context clues to answer your question I’m afraid
Step-by-step explanation:
Answer:
Job has the weakest association with the dependent variable income.
Step-by-step explanation:
The correlation coefficient is used to determine the the strength and direction of the relationship between two variables.
It is denoted by <em>r</em> and the value of <em>r</em> ranges from -1.00 to 1.00.
The correlation data provided is as follows:
Income Education Job Age
Income 1.000
Education 0.677 1.000
Job 0.173 -0.181 1.000
Age 0.369 0.073 0.689 1.000
The dependent variable is the income.
And the variables Education, Job and Age are independent variables.
The correlation between Income and Job is 0.173.
This is the lowest correlation coefficient between the dependent and independent variable.
Thus, Job has the weakest association with the dependent variable income.
