Kostenloser Sampling Error Rechner
Berechnen Sie sampling error for proportions mit confidence intervals. Kostenloser margin of error Rechner for surveys.
Sampling Error
0.049000
Sampling Error vs Proportion (p)
Formel
How to Calculate Sampling Error for Proportions
Formula
Sampling Error = z * sqrt(p * (1-p) / n)
Sampling error is the margin of error in estimating a population proportion from a sample. It depends on the confidence level (z), the proportion (p), and the sample size (n). Maximum error occurs at p = 0.5. The confidence interval is p +/- sampling error.
Lösungsbeispiel
A poll of 400 people finds 50% support (p = 0.5) at 95% confidence.
- 01SE = sqrt(0.5 * 0.5 / 400) = sqrt(0.000625) = 0.025
- 02Sampling error = 1.96 * 0.025 = 0.049
- 03As a percentage: +/- 4.9%
- 04CI: (0.451, 0.549) or 45.1% to 54.9%
Häufig Gestellte Fragen
Why is sampling error maximized at p = 0.5?
The expression p*(1-p) is largest when p = 0.5 (it equals 0.25). As p moves toward 0 or 1, uncertainty decreases because the outcome is more predictable. Using p = 0.5 gives the most conservative (largest) margin of error.
How do I reduce sampling error?
Increase sample size (most effective), accept a lower confidence level (reduce z), or use stratified sampling. Quadrupling n halves the sampling error.
Does sampling error account for all sources of error?
No. Sampling error only covers random sampling variation. Non-sampling errors (bias, non-response, measurement error, question wording) are separate and often more problematic. A large sample does not fix non-sampling errors.
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