Algebra always makes things sound harder than they actually are, and weird vocabulary can mix up the steps we knew so well.
Part 1: Multiply the first equation by a 2 so that you can cancel out the y variable.
6x - 2y = 0
5x + 2y = 22
Part 2: Actually cancel out the y variables, and combine like terms.
11x = 22
Part 3: Solve for "x" by dividing both sides by 11
x = 2
Part 4: Substitute the variable "x" with the value we just solved for in the original equation.
3(2) - y = 0
6 - y = 0
Then, solve for y by adding y to both sides
6=y
Solution Set = {2,6}
Perimeter = 2(width) + 2(length)
w = 5x
l = x + 5
P = 2(5x) + 2(x + 5)
P = 10x + 2x + 10
P = 12x + 10
Answer:
See Explanation
Step-by-step explanation:
The question is incomplete, as the options to select the required condition from were not listed. So, I will answer on general terms
From the question, we understand that the cube has an open-top and the surface ares is 256 in^2
Let L represents the edge length, the surface area (S) is:
Substitute 256 for S
Divide both sides by 5
Take square roots of both sides:
---- approximated
The volume of the cube is:
<em>So, the edge length of the cube is 7.16 inches and the volume is 366.36 cubic inches</em>
<em />
4.560, 4.561, 4.562, 4.563, 4.564......all of these, when rounded to the nearest hundredth = 4.56
Answer:
D. 30
Step-by-step explanation:
Having a population that doesn't follow normal distribution (skewed) can still have sampling distribution that is completely normal. This fact is presented in the Central Limit Theorem.
Central Limit Theorem: states that we can have a normal distribution of sample means even if the original population doesn't follow normal distribution, we just need to take a large sample.
So how much sample size do we need?
There is no straight forward answer to this rather we have to analyse the situation closely!
1. If the population distribution is already normal then a smaller sample size would be enough to ensure normal distribution.
2. If the population distribution is very skewed than a larger number of sample size is needed to ensure normal distribution. The rule of thumb is to take sample size equal to or more than 30 to be on safer side. This is the case in this problem hence option D fits the best.
