Sample mean and covariance

The sample mean (sample average) or empirical mean (empirical average), and the sample covariance or empirical covariance are <a href="/facts/Statistic/av21WaMK">statistics</a> computed from a <a href="/facts/Sample_(statistics)/URCwKNge">sample</a> of data on one or more <a href="/facts/Random_variables/TwTBXnLT">random variables</a>.
The sample mean is the <a href="/facts/Average/etawWjw4">average</a> value (or <a href="/facts/Mean/swcEd4Pg">mean value</a>) of a <a href="/facts/Sample_(statistics)/URCwKNge">sample</a> of numbers taken from a larger <a href="/facts/Statistical_population/KAILs8E3">population</a> of numbers, where "population" indicates not number of people but the entirety of relevant data, whether collected or not. A sample of 40 companies' sales from the <a href="/facts/Fortune_500/BLeHWymz">Fortune 500</a> might be used for convenience instead of looking at the population, all 500 companies' sales. The sample mean is used as an <a href="/facts/Estimator/CbkjcKvN">estimator</a> for the population mean, the average value in the entire population, where the estimate is more likely to be close to the population mean if the sample is large and representative. The reliability of the sample mean is estimated using the <a href="/facts/Standard_error/Iv96AyCD">standard error</a>, which in turn is calculated using the <a href="/facts/Variance/ULBJKXD1">variance</a> of the sample. If the sample is random, the standard error falls with the size of the sample and the sample mean's distribution approaches the normal distribution as the sample size increases.
The term "sample mean" can also be used to refer to a <a href="/facts/Vector_(mathematics_and_physics)/U8mM7A5F">vector</a> of average values when the statistician is looking at the values of several variables in the sample, e.g. the sales, profits, and employees of a sample of Fortune 500 companies. In this case, there is not just a sample variance for each variable but a sample <a href="/facts/Covariance_matrix/kLhgjHC6">variance-covariance matrix</a> (or simply covariance matrix) showing also the relationship between each pair of variables. This would be a 3×3 matrix when 3 variables are being considered. The sample covariance is useful in judging the reliability of the sample means as estimators and is also useful as an estimate of the population covariance matrix.
Due to their ease of calculation and other desirable characteristics, the sample mean and sample covariance are widely used in statistics to represent the <a href="/facts/Location/fXux5RaJ">location</a> and <a href="/facts/Statistical_dispersion/xqevRHmz">dispersion</a> of the <a href="/facts/Probability_distribution/EpsKKVRu">distribution</a> of values in the sample, and to estimate the values for the population.

Sample mean and covariance open-in-new

Sample mean and covariance