An analysis of ore assays about 1.5% iron. What minimum sample mass should be taken if the relative error resulting from a 0.5 Ng loss is not to exceed -2%?
Understand the Problem
The question is asking us to calculate the minimum sample mass needed to ensure that the relative error from a loss of 0.5 Ng does not exceed -2% when analyzing ore assays with an iron concentration of 1.5%. This involves understanding how relative error is determined and how it relates to sample size.
Answer
$25 \, \text{Ng}$
Answer for screen readers
The minimum sample mass needed is $25 , \text{Ng}$.
Steps to Solve
- Define Relative Error Relative error is calculated as the difference between the measured value and the true value, divided by the true value. In this case, the formula can be expressed as follows:
$$ \text{Relative Error} = \frac{\text{Measured Value} - \text{True Value}}{\text{True Value}} $$
- Set Up the Equation From the problem, we know that the relative error must not exceed -2% for a loss of 0.5 Ng. We convert -2% to its decimal form:
$$ -2% = -0.02 $$
- Express the Measured Value Let ( m ) be the true sample mass. Given a loss of 0.5 Ng, the measured value after loss can be expressed as:
$$ m - 0.5 , \text{Ng} $$
Now we can plug this into the relative error formula:
$$ \frac{(m - 0.5) - m}{m} = -0.02 $$
- Simplify the Equation We simplify the equation from step 3:
$$ \frac{-0.5}{m} = -0.02 $$
- Solve for Sample Mass $m$ Now we solve for ( m ):
Multiply both sides by ( m ) and then by -1:
$$ 0.5 = 0.02m $$
Now divide by 0.02:
$$ m = \frac{0.5}{0.02} $$
Calculate the value:
$$ m = 25 , \text{Ng} $$
The minimum sample mass needed is $25 , \text{Ng}$.
More Information
This solution shows how we can determine the necessary sample mass in order to maintain a controlled relative error. Understanding relative error is crucial in various scientific and engineering applications.
Tips
- A common mistake is forgetting to correctly convert percentage values to decimal form, which can lead to incorrect calculations.
- Another mistake is not correctly setting up the equation to reflect the situation accurately, leading to a wrong conclusion.
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