Enter the total discrepancy value and the expected value into the Calculator. The calculator will evaluate the Percent Discrepancy.
Percent Discrepancy Formula
PD = D / EV * 100
Variables:
- PD is the Percent Discrepancy (%)
- D is the total discrepancy value
- EV is the expected value
To calculate Percent Discrepancy, divide the total discrepancy value by the expected value, then multiply by 100.
How to Calculate Percent Discrepancy?
The following steps outline how to calculate the Percent Discrepancy.
- First, determine the total discrepancy value.
- Next, determine the expected value.
- Next, gather the formula from above = PD = D / EV * 100.
- Finally, calculate the Percent Discrepancy.
- After inserting the variables and calculating the result, check your answer with the calculator above.
Example Problem :
Use the following variables as an example problem to test your knowledge.
total discrepancy value = 93
expected value = 1200
Frequently Asked Questions (FAQ)
What is Percent Discrepancy?
Percent Discrepancy is a measure used to express the difference between an observed value and an expected value as a percentage of the expected value. It is commonly used in experiments and statistical analysis to quantify the accuracy of a measurement or a model.
Why is calculating Percent Discrepancy important?
Calculating Percent Discrepancy is important because it provides a standardized way to compare the accuracy of different measurements or models, regardless of their scale. It helps in identifying the reliability of experimental results and in making informed decisions based on the level of discrepancy from expected outcomes.
Can Percent Discrepancy be negative?
Yes, Percent Discrepancy can be negative if the observed value is less than the expected value. A negative Percent Discrepancy indicates that the actual result is lower than what was anticipated.
How can I reduce the Percent Discrepancy in my experiments?
To reduce Percent Discrepancy, ensure that your experimental setup is as controlled as possible, use precise and accurate measurement tools, and repeat the experiment multiple times to average out any anomalies. Additionally, thoroughly review your experimental design and methodology to identify any potential sources of error.
