Finding variance involves calculating the average squared deviation from the mean. This statistical measure quantifies the dispersion or spread of data points in a data set. Understanding variance is essential for assessing data variability and is a foundational concept in statistical analysis and quality control.
1. Calculate the Mean: Determine the mean (average) of your data set.
2. Compute Squared Deviations: Subtract the mean from each data point, square the result, and sum these squared deviations.
3. Divide by the Number of Observations: Divide the total squared deviations by the number of observations (for population variance) or by the number of observations minus one (for sample variance).
What is the variance in our monthly sales figures for the past year?
How does the variance in customer satisfaction scores compare between different regions?
What is the variance in our marketing campaign ROI across different channels?
How does the variance in production costs affect our overall profitability?
