Estimated Mean of a Population

Let's suppose you have several values randomly drawn from some source population (these values are usually referred to as a sample). For a given sample, you can calculate the mean and the standard deviation of the sample. But the question is - what is the mean and the standard deviation of the source population. Intuitively, you feel that, of course, the sample mean isn't equal to the source mean, but they should be somewhat close or in the vicinity of each other.

The calculator below estimates the mean of the population using the sample. The vicinity is found for different confidence levels using Student's t-distribution.

For this to work, the following assumptions should be met:

1. The scale of measurement has the properties of an equal-interval scale.
2. The sample is randomly drawn from the source population.
3. The source population can be reasonably supposed to have a normal distribution.

The formula for estimating mean of a population based on the sample is
, where

- mean of the sample

- t-ratio for the p value which corresponds to chosen confidence level for non-directional test.

It is calculated from the inverse of the CDF for the Student's T distribution with degrees of freedom equals N-1, where N is the number of values in the sample. For example, to get a t-ratio for 0.05 level of significance or 95% confidence level, you need to take the absolute value of the inverse at 0.025.

- an estimate of the standard deviation of the sampling distribution of sample means (or standard error of the mean)

It is calculated as

If you care about how these formulas are derived, you can read an excellent explanation here, starting from Chapter 9.

Estimated Mean of a Population

19.57 23.91 17.8 18.49 14.25 21.73 16.48 15.84 17.5 19.72 22.37 20.35 20.92 18.6 14.03 16.35 22.22 20.06 13.82 20.11 16.01 15.16 18.51 17.08 20.47 16.14 18.6 17.99 13.19 16.42

Sample

Confidence Level95% 98% 99% 99.9%

Calculation precision

Digits after the decimal point: 2

Calculate

Estimated Mean

 

Lower limit

 

Mean of the sample

 

Upper limit

 

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