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The sample mean is the average of the values of a variable in a sample, which is the sum of those values divided by the number of values. Using mathematical notation, if a sample of N observations on variable X is taken from the population, the sample mean is:
In mathematics and statistics, the arithmetic mean (/ ˌ æ r ɪ θ ˈ m ɛ t ɪ k / arr-ith-MET-ik), arithmetic average, or just the mean or average (when the context is clear) is the sum of a collection of numbers divided by the count of numbers in the collection. [1]
The above formula was taken from Sarndal et al. (1992) (also presented in Cochran 1977), but was written differently. [ 2 ] : 52 [ 1 ] : 307 (11.35) The left side is how the variance was written and the right side is how we've developed the weighted version:
In time series analysis used in statistics and econometrics, autoregressive integrated moving average (ARIMA) and seasonal ARIMA (SARIMA) models are generalizations of the autoregressive moving average (ARMA) model to non-stationary series and periodic variation, respectively.
In calculus, and especially multivariable calculus, the mean of a function is loosely defined as the average value of the function over its domain.In one variable, the mean of a function f(x) over the interval (a,b) is defined by: [1]
A Bayesian average is a method of estimating the mean of a population using outside information, especially a pre-existing belief, [1] which is factored into the calculation.
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Exponential smoothing or exponential moving average (EMA) is a rule of thumb technique for smoothing time series data using the exponential window function.Whereas in the simple moving average the past observations are weighted equally, exponential functions are used to assign exponentially decreasing weights over time.