The number of copper atoms in a penny of copper is 6.38×10²² atoms.
Given that,
A penny contains 0.106 mol of copper, how many atoms of copper are in a penny is to be determined.
<h3>What is simplification?</h3>
The process in mathematics to operate and interpret the function to make the function or expression simple or more understandable is called simplifying and the process is called simplification.
Here,
Atom in 1 mole = 6.022×10²³ atom / mole
Number of copper atoms = 0.106 × 6.022×10²³
Number of copper atoms = 6.38×10²² atoms
Thus, the number of copper atoms in a penny of copper is 6.38×10²² atoms.
Learn more about simplification here: brainly.com/question/12501526
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Answer:
Can i see the shapes ?
Step-by-step explanation:
You’re going to have to single out the x. So, the way to go is divide both sides by m. Then you’re left with
x = y/m
Answer:
f(m) = W - 16m
Step-by-step explanation:
f(m) = W - 16m
16 gallons per minute,
So 16m gallons in m minutes
<h3>
Answer: c = 0.0325d</h3>
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Explanation:
For each row, divide the earnings over the sales.
- In row 1, we have 22/673 = 0.0327 approximately
- In row 2, we have 37/1298 = 0.0285 approximately
- In row 3, we have 101/3277 = 0.0308 approximately
- In row 4, we have 150/5180 = 0.0290 approximately
All of these decimal values have the following conversions to percentages
- 0.0327 = 3.27%
- 0.0285 = 2.85%
- 0.0308 = 3.08%
- 0.0290 = 2.90%
If we add up those percentages and divide by 4, we get the average percentage
(3.27+2.85+3.08+2.90)/4 = 3.025
So the average percentage of these four is 3.025%
So for instance, if you made $1000 in sales, then 0.0325*1000 = 32.50 would be the estimated earnings.
A good estimate in my opinion is the equation c = 0.0325d since 3.025% converts to the decimal form 0.0325
Another method you could use is linear regression to help estimate. Though this method is a lot more complicated involving many more steps. It's better to use technology (eg: graphing calculator) if you go this route. The linear regression line is approximately y = 0.02896x + 2.00732; we can see the slope 0.02896 isn't too far off from 0.0325. Other forms of regression are possible as well.