Title: Sample Size Calculator
Headings: Sample Size Calculator
Sample Size Calculator
Find Out The Sample Size
Find Out the Margin of Error
Statistics of a Random Sample
Confidence Level
Confidence Interval
Sample Size Calculation

Content: Confidence Level
The confidence level is a measure of certainty regarding how accurately a sample reflects the population being studied within a chosen confidence interval. The most commonly used confidence levels are 90%, 95%, and 99% which each have their own corresponding z-scores (which can be found using an equation or widely available tables like the one provided below) based on the chosen confidence level. Note that using z-scores assumes that the sampling distribution is normally distributed, as described above in "Statistics of a Random Sample." Given that an experiment or survey is repeated many times, the confidence level essentially indicates the percentage of the time that the resulting interval found from repeated tests will contain the true result. Confidence Level
z-score (±)
0.70
1.04
0.75
1.15
0.80
1.28
0.85
1.44
0.92
1.75
0.95
1.96
0.96
2.05
0.98
2.33
0.99
2.58
0.999
3.29
0.9999
3.89
0.99999
4.42
Confidence Interval
In statistics, a confidence interval is an estimated range of likely values for a population parameter, for example 40 ± 2 or 40 ± 5%. Taking the commonly used 95% confidence level as an example, if the same population were sampled multiple times, and interval estimates made on each occasion, in approximately 95% of the cases, the true population parameter would be contained within the interval. Note that the 95% probability refers to the reliability of the estimation procedure and not to a specific interval. Once an interval is calculated, it either contains or does not contain the population parameter of interest. Some factors that affect the width of a confidence interval include: size of the sample, confidence level, and variability within the sample.