01 Key Concepts
Definition
Standard deviation = square root of variance. It tells you the 'typical' distance of data points from the mean.
Population vs. Sample Standard Deviation
Population standard deviation (sigma) is the square root of population variance; sample standard deviation (s) is the square root of sample variance.
Interpreting Standard Deviation
A small standard deviation means data points are close to the mean; a large one means they're spread out.
Relationship to the Normal Distribution
In a normal distribution, about 68% of data falls within 1 standard deviation of the mean, and about 95% within 2 (the Empirical Rule).
Comparing Datasets
Standard deviation lets you compare the consistency of two datasets even if they have the same mean โ the one with the smaller standard deviation is more consistent.
02 Key Formulas
- Standard deviation = square root of variance
03 Solved Examples
- Standard deviation = square root of variance = sqrt(5).
- A smaller standard deviation indicates scores are closer to the mean, i.e., more consistent.
- Class A's standard deviation (5) is smaller than Class B's (15).
- A standard deviation of 0 means there is no spread at all.
- Every value in the dataset must be identical, equal to the mean.
04 Practice Questions
๐ Standard Deviation โ Downloadable Worksheet
10 questions with a full answer key. Grab the PDF to print, or try the interactive version in your browser.