More Information.

Simple Statistical Analysis



Input data separated by a commas
CLEAR


Calculate Statistics


Population

$$Mean \, \mu = {\sum x \over N} \, = \,$$
9.333
$$Variance \, \sigma^2 = {\sum(x - \mu)^2 \over N} \, = \, $$
43.111
$$Standard \, Deviation \, \sigma = \sqrt{{\sum(x - \mu)^2 \over N}} \, = \, $$
6.566

Sample

$$Mean \, \bar{x} = {\sum x \over n} \, = \,$$
9.333
$$Variance \, s^2 = {\sum(x - \bar{x})^2 \over n-1} \, = \, $$
48.5
$$Standard \, Deviation \, s = \sqrt{{\sum(x - \bar{x})^2 \over n-1}} \, = \, $$
6.964

Simple Statistics Page



This is probably the most basic statistical analysis of a set of data you will come across. To use this you need to add numbers only data separated by commas with or without spaces. I've provided the statistics for complete data sets and samples from a data set.

Mean This is what most people call call the average, that is the sum of the data divided by the number of data points.

Variance This is an indication of how far a set of numbers range from the mean of the set.

Standard Deviation This is simply the square root of the variance so basically a scaled down indication of the spread of data either side of the mean.

Variance and standard deviation are calculated differently for whole population data sets and sample data sets. This is because samples are considered more likely to contain outlying data so the indications of deviation from the mean are arbitrarily reduced. On this page you can compare the two