| Arithmetic mean | The sum of observations divided by the total number of observations.
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| Chebyshev's theorem | For any set of observations (sample or population), the minimum proportion of the values that lie within k standard deviations of the mean is at least 1 - 1/k2, where k is any constant greater than 1.
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| Empirical Rule | For a symmetrical, bell-shaped frequency distribution, approximately 68 percent of the observations will lie within plus and minus one standard deviation of the mean; about 95 percent of the observations will lie within plus and minus two standard deviations of the mean; and practically all (99.7 percent) will lie within plus and minus three standard deviations of the mean.
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| Geometric mean | The nth root of the product of n values.
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| Mean Deviation | The mean of the absolute values of the deviations from the arithmetic mean.
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| Measure of location | A single value that summarizes a set of data. It locates the center of the values.
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| Median | The midpoints of the values after all observations have been ordered from the smallest to the largest, or from largest to smallest. Fifty percent of the observations are above the median and 50 percent are below the median.
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| Mode | The value of the observation that appears most frequently.
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| Negatively skewed distribution | The long tail is to the left or in the negative direction. The mean is smaller than the median or mode.
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| Parameter | A characteristic of a population.
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| Positively skewed distribution | The long tail is to the right; that is, in the positive direction. The mean is larger than the median or the mode.
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| Range | The difference between the largest and smallest values in a data set.
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| Standard Deviation | The square root of the variance.
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| Statistic | A characteristic of a sample.
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| Weighted mean | The value of each observation is multiplied by the number of times it occurs. The sum of these products is divided by the total number of observations to determine the weighted mean.
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| Symmetrical distribution | A distribution that has the same shape on either side of the median.
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| Variance | The arithmetic mean of the squared deviations from the mean.
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