1. What Is Percentage Deviation?

Percentage deviation is a statistical measure that quantifies the difference between a measured value and an expected value as a percentage of the expected value. It helps assess the accuracy and precision of measurements in various fields.

2. How Does The Calculator Work?

The calculator uses the percentage deviation formula:

Where:

• \( \text{Measured} \) — The actual observed or measured value
• \( \text{Expected} \) — The theoretical or expected value

Explanation: The formula calculates the absolute difference between measured and expected values, divides by the expected value, and multiplies by 100 to express as a percentage.

3. Importance Of Percentage Deviation

Details: Percentage deviation is crucial for quality control, experimental validation, and performance measurement across scientific, industrial, and business applications. It helps identify variations from expected outcomes.

4. Using The Calculator

Tips: Enter both measured and expected values as positive numbers. The expected value must be greater than zero for valid calculation.

5. Frequently Asked Questions (FAQ)

Q1: What does a 0% deviation indicate?
A: A 0% deviation indicates perfect agreement between measured and expected values, meaning no difference exists.

Q2: How is percentage deviation different from percentage error?
A: Percentage deviation typically refers to the absolute difference as a percentage, while percentage error may consider direction (positive/negative) in some contexts.

Q3: What is considered an acceptable percentage deviation?
A: Acceptable deviation varies by industry and application. Scientific experiments might accept ±5%, while manufacturing may require tighter tolerances like ±1%.

Q4: Can percentage deviation be negative?
A: The standard formula uses absolute value, so percentage deviation is always positive. Some variations may preserve the sign to indicate direction.

Q5: When should I use percentage deviation vs absolute deviation?
A: Use percentage deviation when you need to compare variations across different scales or units. Absolute deviation is better for same-scale comparisons.