Key Facts
- Category
- Math, Date & Finance
- Input Types
- select, text, number
- Output Type
- json
- Sample Coverage
- 4
- API Ready
- Yes
Overview
The Sample Size Calculator helps you determine the statistically significant number of participants needed for your research, surveys, or experiments. By inputting your desired confidence level and margin of error, you can ensure your data collection is robust and reliable.
When to Use
- •Before launching a survey to ensure your results are representative of the target population.
- •When planning a scientific experiment to determine the minimum number of subjects required for valid conclusions.
- •When you need to adjust your sample size based on a known, finite population size to avoid over-sampling.
How It Works
- •Select your calculation mode: choose 'Proportion' for categorical data or 'Mean' for continuous numerical data.
- •Input your target confidence level (e.g., 95%) and the acceptable margin of error.
- •Provide optional parameters like estimated standard deviation or total population size for more precise results.
- •Click calculate to receive the recommended sample size based on statistical formulas.
Use Cases
Examples
1. General Survey Planning
Market Researcher- Background
- Planning a customer satisfaction survey for a large user base.
- Problem
- Needs to know how many users to contact to achieve a 95% confidence level with a 5% margin of error.
- How to Use
- Set mode to 'Proportion', confidence level to 95%, and margin of error to 0.05.
- Example Config
-
calculatorMode: proportion, confidenceLevel: 0.95, marginOfError: 0.05 - Outcome
- The tool recommends a sample size of 385 participants.
2. Finite Population Study
Operations Manager- Background
- Auditing a specific batch of 500 manufactured parts.
- Problem
- Needs to determine the sample size for an inspection with a 2-unit margin of error.
- How to Use
- Set mode to 'Mean', confidence level to 95%, margin of error to 2, and population size to 500.
- Example Config
-
calculatorMode: mean, confidenceLevel: 0.95, marginOfError: 2, populationSize: 500 - Outcome
- The tool provides an adjusted sample size of 125 units, accounting for the finite population.
Try with Samples
barcodeRelated Hubs
FAQ
What is a confidence level?
It represents how certain you want to be that the true population parameter falls within your margin of error, typically set at 95%.
What is the margin of error?
It is the range of values above and below your sample result that you expect the true population value to fall within.
When should I use the finite population correction?
Use this when your total population is small and known, as it allows for a smaller sample size while maintaining the same level of accuracy.
What is the difference between Proportion and Mean modes?
Proportion mode is for binary outcomes (e.g., yes/no), while Mean mode is for measuring averages of continuous variables.
Why is the recommended sample size sometimes a decimal?
Calculations often result in fractions; always round up to the nearest whole number to ensure your sample size meets the minimum statistical requirement.