Graphical Summary
Table of Statistics - Standard Deviation (Stdev) and Variance
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Graphical SummaryTable of Statistics - Standard Deviation (Stdev) and Variance |
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The standard deviation and variance measure dispersion, or how far the observations in a sample deviate from the mean. The standard deviation is analogous to an average distance (independent of direction) from the mean. The variance is simply the standard deviation squared.
Like the mean, the standard deviation (as well as the variance) is very sensitive to extreme values.
Example Output |
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Anderson-Darling Normality Test A-Squared: 0.99 P-Value: 0.008
Mean 3.6364 StDev 2.3779 Variance 5.6545 Skewness 2.11078 Kurtosis 5.61936 N 11
Minimum 1.0000 1st Quartile 2.0000 Median 3.0000 3rd Quartile 4.0000 Maximum 10.0000
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The standard deviation and variance are listed in the middle right of the Graphical Summary.
Interpretation |
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The standard deviation for the precipitation data is 2.3779. This tells you that on average, the values in the data set tend to differ from the mean by + 2.3779.
The variance for the precipitation data is 5.6545.
The large value of 10 days with precipitation for April increases the standard deviation quite a bit. Without this value, the standard deviation would be 1.155 instead of 2.3779. Conversely, if April had 30 days of rain, the standard deviation would be 8.210!
