How many people do you need to take your survey? Determining sample size can be tough. Try our sample size calculator; We give you everything you need to to calculate how many responses you need to be confident in your results.

# Sample Size Calculator

Population Size: | ||

Confidence Level: | ||

Margin of Error (%): (Also called confidence interval or percent error) | ||

#### Needed Sample Size:

Based on your population

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#### Needed Sample Size:

Based on infinite (large) population

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* Assumes a normal distribution of 50% to calculate your sample size

There can be two different sample sizes. One based on an infinitely large population, the other based on a smaller finite population. This finite number you can specify above.

The bigger the population is, the bigger the sample will need to be to accurately reflect the population.

Population Size: This is the total number of people in the group you are trying to reach with your survey. If you were taking a random sample of people in the United States, then your population size would be about 321 million.

Confidence Level: A measure of how confident you are that your sample accurately reflects the population, within its margin of error. Common standards used by researchers are 90%, 95%, and 99%.

If your confidence level is 95% in the above example, you could say your 95% certain that between 38% and 42% of the United States Population do not like their jobs.

Margin of Error (Also called percent error): A percentage that describes how closely the answer your sample gave is accurate if you were to ask the entire population. For example, let’s say you send a survey to 500 people in the United States asking them if they like their jobs. 40% say no. If your margin of error is 2% you could say you're confident the true answer is somewhere between 38% and 42%. "How" confident you are can also be described as a percent and this is called a confidence Level.

See our percent error calculator for how to calculate your percent error.

Population Proportion: This can be described as the makeup of the population. For example, if it's well known 60% of college students are female you could say the population proportion of college students is 60% female. If you wanted to mainly get opinions of college females, you would you this 60% number in the formula below (for P). Most times though these numbers are not known and 50% (.50) is used for P. This .5 number produces the largest possible sample size, as it is most conservative.

Finite Population Adjustment: If you know the exact population number for the group you are targeting, an adjustment to sample size will be made to reflect this population number. See the below formulas.

The z-score is the number of standard deviations a given proportion is away from the mean. To find the right z-score to use, refer to the table below:

Desired Confidence Interval | Z-score |

80% | 1.28 |

85% | 1.44 |

90% | 1.65 |

95% | 1.96 |

99% | 2.58 |

Now that you know how many responses you need, work backwards to know how many people you need to reach or send it out to. A response rate of 20% is good while a response rate of 30% is above average. Take you needed sample size and divide it by you expected response rate percentage.