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N = Population size

x_i = ith individual value of variable x

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f_i=Frequency of the nth value of the discreate variable

k=The number of different values for the discreate variable

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x = Sample mean (pronounced "x-bar")

n = Sample size

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i = the index point in the data set corresponding to

     the median value

n = sample size

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w_i = The weight of the ith data value

x_i = The ith data value

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w_i = The weight of the ith data value

x_i = The ith data value

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p = Desired percent

n = Number of values in the data set

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μ = Population mean

N = Population size

σ² = Population variance (sigma squared)

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μ = Population mean

N = Population size

σ = Standard deviation (sigma)

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n = Sample size

s² = Sample variance

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x = Sample mean

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n = Sample size

s = Sample stardard deviation

_

x = Sample mean

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x = Original data value

μ = Population mean

σ = Population standard deviation

z = Standard score (number of standard deviations

      x is from μ)

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x = Original data value

s = Sample standard deviation

z = The standard score

_

x = Sample mean

Regardless of how data are distributed, at least (1 - 1/k²) of the values will fall within k standard deviations of the mean.

The number of standard deviations a value is from the mean.  Standardized data values are sometimes referred to as z-scores

If the data distribution is bell-shaped, then the interval

μ ± 1σ contains approximately 68% of the values

μ ± 2σ contains approximately 95% of the values

μ ± 3σ contains virtually all of the data values.

The population variance is the average of the squared distances of the data values from the mean.

The positive squared deviation is the positive square root of the variance

Quartiles in a data array are those values that divide the data set into four equal-sized groups.  The median corresponds to the second quartile.

The pth percentile in a data array is a value that divides the data set into two parts.  The loer segment contains at least p%, and the upper segement contains at least (100 - p)%, of the data.  The 50th percentile is the median.

A center value that divides a data array into two halves. 

We use ˜μ to denote the population median and M_d to denote the sample median. 

It is not sensitive to extreme values.

Negative Skew

(Left-Skewed)

Posivite Skew

(Right-Skewed)