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Overview
Standard Deviation and Variance
See how standard deviation and variance measure how spread out a data set is, with clear formulas and a full step-by-step worked example.
What You'll Learn
Calculate the mean of a data set as the starting point for every spread measure
Find each deviation by subtracting the mean from every data value
Apply the mean absolute deviation formula by averaging the absolute values of the deviations
Compute variance by averaging the squared deviations, using n for a population and n minus 1 for a sample
Calculate standard deviation by taking the square root of the variance
Compare population and sample formulas to know which one to use for a given problem
What You'll Practice
1
Computing standard deviation and variance for complete data sets
2
Selecting sample data points and calculating sample standard deviation
3
Comparing graphs to determine which has highest or lowest standard deviation
4
Working with frequency tables to find mean and variance
5
Using calculator statistics functions to verify results
Why This Matters
Understanding standard deviation is essential for analyzing data spread in statistics, science, and real-world applications. You'll use these skills to interpret test scores, compare data consistency, analyze research results, and make informed decisions based on variability in any field that uses data.
Before You Start — Make Sure You Can:
This Unit Includes
5 Video lessons
Practice exercises
Learning resources
Skills
Standard Deviation
Variance
Population vs Sample
Mean
Data Spread
Frequency Tables
Statistical Analysis
NS Curriculum Aligned