Any statistical measure relating to the population which is based on all units of the population is called parameter, e.g., population mean ().1), population S.D. (cr), moments µ_{r}, µ_{r} ‘ etc.

Any statistical measure relating to the sample which is based on all units of the sample is called statistic, e.g., sample mean (.X), sample variance, moments m_{r}, m'_{r} etc. Hence the value of a statistic varies from sample to sample. This variation is called 'sampling fluctuation'. The parameter has no fluctuation and it is constant. The probability distribution of a statistic is called 'sampling distribution'.

The standard deviation (S.D.) in the sampling distribution is called 'standard error' of the statistic.

**Example 1.** For a population of jive units, the values of a characteristic x are given below :

8, 2, 6, 4 and 10.

Consider all possible samples of size 2 from the above population and show that the mean of

the sample means is exactly equal to the population mean.

**Solution.** The population mean, )µ = 30/5 = 6

Random samples of size two (Without Replacement)

:. Mean of sample means =(31+29)/10 = 60/10 = 6 which is equal to the population mean.