Erro Amostragem
- Created by
- Renato Passos, Eng. de Software
- Reviewed by
- Renato Passos, Eng. de Software
Last updated: Apr 18, 2026
About this calculator
The Sample Error Calculator helps to calculate the variance of the error in a sample. Sample error is a fundamental concept in statistics, especially in surveys and experiments.
To calculate the sample error, the formula E = z·σ/√n is used, where E is the sample error, z is the Z-test value, σ is the population variance and n is the sample size. This formula is based on the normal distribution and is widely used in statistics.
The sample error is important because it helps to determine the accuracy of the sample. A low sample error indicates that the sample is representative of the population. On the other hand, a high sample error may indicate that the sample is not representative or that there is some source of error.
Here, you can calculate the sample error using known values. This is useful in practical cases, such as market research or scientific experiments.
Frequently asked questions
What is the sample error?
The sample error is the variance of the error in a sample and is calculated using the formula E = z·σ/√n.
When to use the sample error calculator?
The sample error calculator can be used in market research, scientific experiments and in any situation where you need to calculate the variance of the error in a sample.
What is the Z-test value?
The Z-test value is a value that indicates the probability that the sample is representative of the population. It is used in the formula E = z·σ/√n to calculate the sample error.
What is the difference between sample error and population variance?
The population variance is a measure of the dispersion of the population, while the sample error is a measure of the dispersion of the sample in relation to the population.
Can I use the sample error calculator with non-normally distributed samples?
No, the sample error calculator assumes that the sample is normally distributed. If your sample is not normally distributed, you will need to use a different formula to calculate the sample error.