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Kurtosis
4
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N
(
N
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1
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x
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x
3N  12
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i
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
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 (N  1)(N  2)(N  3)   s   N  2N  3
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Kurtosis measures the peakedness of the data. A
normally distributed sample has a Kurtosis equal to zero.
A highly peaked distribution is called leptokurtic and has
positive kurtosis. A relatively flat (thick tailed)
distribution is called platykurtic and has negative
kurtosis. A moderately peaked distribution is called
mesokurtic.
SE_Kurtosis
Standard Error of Kurtosis depends on sample size, not
data values.
Mode, Mode Count
Mode
Mode is the most common value. If a tie exists for
multiple values, there is no mode.
Mode Count
Mode Count is the occurrences of the Mode. If there is
a tie, this value is shown, but Mode is blank.
Confidence Intervals
Confidence Intervals Options
Confidence intervals are used to estimate the population mean from sample
data. The sample is assumed to contain sampling variability, so its mean is
not necessarily the population mean. Confidence intervals estimate the
value of the population mean with an expected degree of accuracy. For
instance, one may describe the mean as having a 95% chance of being 52 ±
5, where 95% is the confidence interval, 52 is the sample mean, and 5 is the
confidence interval band width. As the sample size increases, this band
becomes smaller. Similarly, the band increases as the confidence interval
(%) increases.
Intervals
There are two possible confidence intervals to select. You can either select
the check box for the 95% interval or type in your own interval (between 1
and 99.999%). Type in whole numbers (e.g. type 50 for 50% not 0.5).
48  Chapter 5: Parametric Analysis
Total Access Statistics