Answer:
3(a - b)(a + b)
Step-by-step explanation:
Factorize: (2a - b)² - (a - 2b)²
- Different of Perfect a Square rule: a² - b² = (a + b)(a - b)
(2a - b)² - (a - 2b)² = [(2a - b) + (a - 2b)] × [(2a - b) - (a - 2b)]
1. Distribute and Simplify:
Distribute the (+) sign on the first bracket and simplify: [(2a - b) + (a - 2b)] → 2a - b + a - 2b → (3a - 3b)
Distribute the (-) sign on the first bracket and simplify: [(2a - b) - (a - 2b)] → 2a - b – a + 2b → (a + b)
We now have:
(3a - 3b)(a + b)
2. Factor out the Greatest Common Factor (3) from 3a - 3b:
(3a - 3b) → 3(a - b)
3. Add "(a + b)" back into your factored expression:
3(a - b)(a + b)
Hope this helps!
Answer:
You can get 6 tacos.
Step-by-step explanation:
Since you do not want any burritos this is excess information. All we care about is the tacos which cost $2. We have twelve dollars so $12 divided by $2 equals 6.
Brainliest always helps!
If we say A = ream of paper and B = cost of ink than we can set-up an expression to calculate when A is equal to a number what the number of B will be.
Maximim of 270$ so anything we buy must be equal to this.
Ream of paper cost 6$ each so 6A represents the number of reams bought since we said A is number of reams of paper.
Ink Cartridges are 18$ each so 18B would represent this based on B = to cost of ink.
Now setting up our equation
6A + 18B = 270
When A = 1
B = 14.67 Ink Cartridges
When A = 1 Ream ofpaper
Answer:
Yes.
Step-by-step explanation:
10% is 0.10 in decimal form. Therefore, once he pays the $17.80 setup fee and then 0.20f (or $0.20 per flyer), then we would multiply by 10% (Or 0.10).
In conclusion:
Yes. 0.10( 17.50 + 0.20f ) does represent the total cost of the print job.
Answer:
Step-by-step explanation:
If repeated sample sizes of large sizes are taken at random, and proportion P is calculated for samples the sample mean will have a normal distribution irrespective of the original distribution.
In other words, the sample proportion will follow a normal distribution with mean = p-hat and std deviation =
This is a direct corrollary of central limit theorem for sample means.
Hence we have irrespective of sample size, sample proportion will have expected value same as p-hat.
So whether sample size is 500 or 100 the p hat will have the same distribution.