# Margin of Error Calculator

Enter the confidence level, sample size, sample proportion, and population size to find the margin of error using the calculator below.

## Margin of Error:

### Steps to Solve

#### Margin of Error Formula

#### Step One: Find the Z-Score

z-Score = ?

#### Step Two: Find the Margin of Error

MOE = z · (p̂ · (1 - p̂)) ÷ n

## How to Find the Margin of Error

In statistics, the margin of error is the amount of error in random sampling surveys. Because surveys are often done on a sample of a larger population, there will inevitably be some amount of error.

A lower margin of error produces higher confidence levels in a survey sample. Thus, the margin of error is a good indicator of the confidence you can have in the results of the sample.

The margin of error is expressed as a percentage indicating the degree that the sample results differ from the total population, for instance when calculating a confidence interval.

### Margin of Error Formula

The margin of error is equal to the z-score for the confidence level times the margin of error. You can find the margin of error using the following formula:

Where:

z = z-score for the confidence level

σ² = variance

n = sample size

Thus, the margin of error is equal to the z-score *z* times the square root of the variance *σ²* divided by the sample size *n*. You can find the z-score for your desired confidence level in the table below.

While you can calculate variance using a calculator, you can also use the sample proportion to calculate it. The sample proportion is denoted p̂ and represents the percentage of the sample that has the characteristic you’re interested in.

The variance *σ²* can be expressed with the formula σ² = p̂ · (1 – p̂), where p̂ is the sample proportion.

By substituting the formula for variance using the sample size into the formula above, the margin of error formula becomes:

Where:

z = z-score for the confidence level

p̂ = sample proportion

n = sample size

Thus, the margin of error is equal to the z-score *z* times the standard error, which is the square root of the sample proportion *p̂* times 1 minus the sample proportion *p̂*, divided by the sample size *n*.

### Example

Let’s find the margin of error for a survey asking people what their favorite color is. The survey sampled 250 people, and 40% of respondents answered that their favorite color was red. We want a 95% confidence level in the margin of error.

Start by assigning values to the variables needed for the formula.

z = 1.96 (95% confidence = 1.96 [table])

p̂ = 0.4 40% ÷ 100 = 0.4

n = 250 sample size

Next, substitute the variables in the formula and solve.

MOE = 1.96 · √(0.4 · (1 – 0.4) ÷ 250)

MOE = 1.96 · √(0.4 · 0.6 ÷ 250)

MOE = 1.96 · √0.00096

MOE = 1.96 · 0.03098

MOE = 0.06073

Then, multiply the margin of error by 100 to convert it to a percentage.

MOE = 0.06073 × 100 = 6.073%

Thus, the margin of error is equal to ±6.073%. Or rather, We are 95% confident that 40% of the total population has the favorite color of blue, plus or minus 6.073%.

### Z-Scores

The table below shows the z-scores for various confidence levels.

Confidence Level | Z-Score |
---|---|

70% | 1.04 |

75% | 1.15 |

80% | 1.28 |

85% | 1.44 |

90% | 1.645 |

91% | 1.7 |

92% | 1.75 |

93% | 1.81 |

94% | 1.88 |

95% | 1.96 |

96% | 2.05 |

97% | 2.17 |

98% | 2.33 |

99% | 2.576 |

99.9% | 3.29 |