Answer:
Step-by-step explanation:
<u>Common Factors</u>
An algebraic expression that is formed by sums or subtractions of terms can be factored provided there are numeric or variable common factors in all the terms.
The following expression
Can be factored in the constants and in the variable x.
1. To find the common factor of the variable, we must locate if the variable is present in all terms. If so, we take the common factor as the variable with an exponent which is the lowest of all the exponents found throughout the different terms. In this case, the lowest exponent is x (exponent 1).
2. To find the common factors of the constants, we take all the coefficients:
12 - 20 - 32
and find the greatest common divisor of them, i.e. the greatest number all the given numbers can be divided by. This number is 4, since 12/4=3, 20/4=5 and 32/4=8
3. The factored expression is
Answer:
The answer is D.
Step-by-step explanation:
The first thing I did was substitute the variables in for x and y. This is the numbers in the answer choices: (x,y). I don't know if there is an easier way to do this, but you can replace the two numbers in for the variables since it's multiple choice.
For example,
A: -2+2*4=6 Isn't right
B: 1+2*-1= -1 Nope
C: (0,0) you can already tell it's not right because anything multiplied by 0 is 0.
D: -4+2*1=-2 This is the correct answer.
Answer:
45 mins
Step-by-step explanation:
The question is how much time should the painter spend on painting a doll for the costs to still be equal or lower to $24.50
We can make this equation, representing the raw materials + the painting job (at $18/h):
$11 + $18x = $24.50
18x = 13.50
x = 13.5 / 18 = 0.75
So, the painter should spend at most 3/4 of an hour (or 45 mins) painting a doll to keep the cost at or below $24.50 per doll.
Answer:
(D) Quantitative
Step-by-step explanation:
Bivariate data involves two types of variables. Categorical data will have a number of different categories. Continuous data usually includes a range of values so is likely to be in decimals. Quantitative data will be collected in this scenario as it will be calculated the number of times each shirt is tried on.
