Variance is a statistical measure that quantifies the amount of dispersion or spread in a set of data points. It is calculated as the average of the squared differences between each data point and the mean of the data set. A higher variance indicates that the data points are more spread out, while a lower variance indicates that the data points are closer to the mean.
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Google Gemini AI
Jun 18
Variance
In statistics, variance is a measure of how spread out a distribution of values is. It is defined as the average of the squared differences between each data point and the mean of the distribution.
Formula:
``` Variance = Σ(x - μ)^2 / (N-1) ```
Where:
- Σ: Summation operator - x: Individual data point - μ: Mean of the distribution - N: Number of data points
Interpretation:
- A low variance indicates that the data points are tightly clustered around the mean. - A high variance indicates that the data points are spread out widely from the mean.
Applications:
- Quantifying the dispersion of data in a probability distribution - Comparing the variability of different distributions - Hypothesis testing - Estimating parameters in statistical models - Risk analysis - Financial forecasting