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How to Calculate Percentage Deviation

Percentage Deviation Formula:

\[ PD = \frac{|measured - expected|}{expected} \times 100\% \]

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1. What is Percentage Deviation?

Percentage Deviation (PD) measures how much a measured value differs from an expected value, expressed as a percentage of the expected value. It's commonly used in quality control, scientific experiments, and statistical analysis.

2. How Does the Calculator Work?

The calculator uses the percentage deviation formula:

\[ PD = \frac{|measured - expected|}{expected} \times 100\% \]

Where:

Explanation: The absolute difference between measured and expected values is divided by the expected value and multiplied by 100 to get a percentage.

3. Importance of Percentage Deviation

Details: Percentage deviation helps quantify accuracy and precision in measurements. It's widely used in laboratory settings, manufacturing quality control, and scientific research to assess measurement reliability.

4. Using the Calculator

Tips: Enter both measured and expected values. The expected value cannot be zero (division by zero is undefined). Values can be positive or negative, but the deviation is always reported as a positive percentage.

5. Frequently Asked Questions (FAQ)

Q1: What's a good percentage deviation?
A: Acceptable ranges vary by field. In many lab settings, <5% is excellent, 5-10% is acceptable, and >10% may indicate problems.

Q2: How is this different from percent error?
A: They're essentially the same calculation, though sometimes "error" implies a known correct value while "deviation" may refer to variation from a mean.

Q3: Can percentage deviation be negative?
A: No, the absolute value ensures the deviation is always positive, showing magnitude without direction.

Q4: What if my expected value is zero?
A: The calculation is undefined when expected value is zero. Consider using absolute difference instead in such cases.

Q5: How does this relate to standard deviation?
A: Standard deviation measures spread in a dataset, while percentage deviation compares a single measurement to an expected value.

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