Data Science Course > Measures of Central Tendency and Variability

Application of Standard Deviation in Data Science

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The standard deviation (σ) is a measure of the distribution's spread. The wider the spread, the higher the standard deviation. The square root of variance is used to compute the standard deviation for a discrete set of values.

The standard deviation, along with the mean, is used to summarise continuous data rather than categorical data. Furthermore, like the mean, the standard deviation is usually only used when the continuous data is not highly skewed or has outliers.

In statistics, variance and standard deviation are used to calculate the data's variability, or how the values vary around the mean.

Standard deviation formula:

  • SD = (x-x̄)/√N
  • Where x and x̄ are the scores for each item in the data set, and N is the number of items in the data set.
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  7. Cross Tabulation in Data Science
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  1. Measures of Central Tendency and Variability in Data Science
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  2. Mean and Percentiles in Data Science
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  3. Quartiles in Data Science
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  4. Measures of Variability in Data Science
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  5. Variance and Standard Deviation in Data Science
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  6. Application of Standard Deviation in Data Science
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  7. Z-score and Co-efficient of Variation in Data Science
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