What Is Margin of Error?
The margin of error (MOE) expresses the maximum expected difference between a sample statistic and the true population parameter at a specified level of statistical confidence.
1. Margin of Error for Proportions (%)
MOE=z* × √[ p(1 − p) / n ](× √[(N − n)/(N − 1)] if FPC)
2. Margin of Error for Population Means
MOE=
z* × σ√n
Step-by-Step Calculation Breakdown (Example: n = 1,000, 95% Confidence, p = 50%)
Step 1: Identify Critical Value (z*) for 95% Confidence
• For 95% confidence (α = 0.05), critical value z* = 1.960
Step 2: Calculate Standard Error of Proportion
• SE = √[ (0.50 × 0.50) ÷ 1000 ] = √[ 0.25 ÷ 1000 ] = √0.00025 = 0.01581 (1.581%)
Step 3: Multiply Critical Value by Standard Error for Final MOE
• MOE = 1.960 × 1.581% = ±3.10%
• 95% Confidence Interval = [50% − 3.10%, 50% + 3.10%] = [46.90%, 53.10%]
Key Drivers of Margin of Error
- Sample Size (n): Increasing sample size shrinks uncertainty exponentially.
- Confidence Level (1 − α): Demanding higher confidence widens the interval to ensure coverage.
- Population Variability (p or σ): For proportions, variability peaks at p = 50%, producing the most conservative (widest) margin of error.