Calculate Data Spread and Variability
Calculate the Mean Absolute Deviation (MAD) to measure the average distance between each data point and the mean. Our calculator helps you understand data variability in statistics, quality control, and data analysis.
Welcome to our Mean Absolute Deviation (MAD) Calculator! This tool helps you calculate the average distance between each data point and the mean, providing a measure of variability in your dataset.
Mean Absolute Deviation (MAD) is a measure of variability in a dataset that calculates the average distance between each data point and the mean.
For a set of values X = {x₁, x₂, ..., xₙ}, the Mean Absolute Deviation is calculated as:
MAD = (Σ|xᵢ - μ|) / n
Where μ is the mean of the dataset and n is the number of values.
For more advanced statistical analyses or complex calculations, you might find our online TI-84 graphing calculator helpful. It offers a wide range of functions for in-depth data analysis and visualization.
Mean Absolute Deviation (MAD) measures how spread out values are from their average. Formula: MAD = (Σ|xi - mean|) / n, where xi is each value, mean is the average, and n is the number of values. Lower MAD indicates data clustered near the mean; higher MAD shows greater spread.
Both measure variability, but MAD uses absolute values while standard deviation uses squared differences. MAD is more robust to outliers and easier to interpret. Standard deviation is more common in statistical inference. Use MAD when you need resistance to extreme values.
MAD is used in: quality control to detect process variation, finance to measure investment risk, weather forecasting for prediction accuracy, manufacturing for tolerance analysis, and data science for identifying anomalies. It provides intuitive understanding of data consistency.
