<span>4.5 g
56.25 g
Since the only type of measurement mentioned in this question is weight or mass, I'll assume that the percentage concentration is % m/m (mass/mass). For that type of concentration measurement, simply multiple the percentage by the total mass to get the mass of the desired substance. So
150 g * 3% = 150 g * 0.03 = 4.5g
For the amount of 8% solution with the same amount of dry substance, there's 2 ways of calculating the mass of solution.
First, use the ratio of percentages, multiplied by the mass of the original solution to get the desired amount of new solution:
3/8 * 150 g = 56.35 g
Or calculate it from scratch, like
4.5/X = 8/100
450/X = 8
450 = 8X
56.25 = X
In both cases, the result is that you desire 56.25 grams of 8% solution.</span>
Answer:
Therefore, we use the linear depreciation and we get is 17222.22 .
Step-by-step explanation:
From Exercise we have that is boat $250,000.
The straight line depreciation for a boat would be calculated as follows:
Cost boat is $250,000.
For $95,000 Deep Blue plans to sell it after 9 years.
We use the formula and we calculate :
(250000-95000)/9=155000/9=17222.22
Therefore, we use the linear depreciation and we get is 17222.22 .
It will be $117...i dont really understand how u wrote it but i added all the numbera and got that amount
Answer:
- Keisha’s experimental probability is 1/50.
- When the inventory is 4000 clocks, the prediction is that 3920 clocks will work.
- Keisha will have more than 97% of the products working.
Step-by-step explanation:
These are three prediction that Keisha can make based on the report that said 6 of 300 clocks tested weren't working.
Base on that information, Keisha can calculate an experimental probability, dividing <em>clocks that don't work properly </em>by <em>the total amount of clocks</em><em>:</em>
<em>
</em>
Therefore, the probability of success is 100% - 2% = 98%.
This means that Keisha has a probability of having 98% of all clocks functioning properly. So, she can make the prediction:<em> from 4000 clocks, 3920 will work. </em>Also, she can predict that she will actually have more than 97% working, because the experimental probability is higher than that.
