arithmetic mean

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Related to Sample means: Central limit theorem

a·rith·me·tic mean

the mean calculated by adding a set of values and then dividing the sum by the number of values.

arithmetic mean

See mean.

mean

Statistics
noun The sum of the values of all observations or data points divided by the number of observations; an arithmetical average; the central tendency of a collection of numbers, which is a sum of the numbers divided by the amount of numbers the collection.

Types
• Population mean (µ).
• Sample mean (x-bar).
 
Vox populi-UK
adjective Stingy; miserly; unwilling to share.

Vox populi-US
adjective Unkind, spiteful.

arith·me·tic mean

(ar'ith-met'ik mēn)
The mean calculated by adding a set of values and then dividing the sum by the number of values.
Synonym(s): average (2) .
Arithmetic meanclick for a larger image
Fig. 47 Arithmetic mean . In this example, the mean (x) of 4 values of x is 11.

arithmetic mean

or

mean

a number (symbol: x) that is computed by calculating the sum of a set of numbers (Σx ) and dividing the sum by the number of terms (n ).

arithmetic mean

see mean.
References in periodicals archive ?
Although the maximum likelihood method is the preferred method for fitting distributions, because the sample mean is unknown for each of the data sets in Table 1, the maximum likelihood method cannot be used to fit the distributions.
A random sample will be generated and displayed in the top window; its mean will be calculated and displayed in both windows; the new mean will be added to the current pool of sample means and the histogram in the bottom window will be updated accordingly.
The approximate normality of the sample mean for large samples is routinely used for calculating confidence limits on actual casino win from a table game, or actual casino win from a given player (Hannum and Cabot, 2005).
If in the sample I have extreme values, the sample mean may be way off the population mean.
Choice of [alpha] is a way of stating how far--in statistical distance--the sample mean must be from what the population mean would be if the null hypothesis were true in order to reject the null hypothesis.
So our sample mean and variance (statistics) are approximations of the true population mean and variance (parameters.
Most researchers analyze RT data by conducting an analysis of variance (ANOVA) on the sample mean (Van Zandt, 2002): this type of statistical approach may not be effective, however, owing to the particular characteristics of RT data.
Construct and examine the distribution of the sample means.
In the same way, for each sample of size n, a sample mean is obtained (11).
It is worth pointing out that when sample means are compared, the sample mean for activities between events is the lowest in table 23.
CC scores for this cluster (M = 1262; SD = 181) ranged near or below the sample mean, while TP scores (M = 824; SD = 179) all fell below the sample mean.
A paired sample t test comparison of the sample means of the ATL (8.