While measures of central tendency like the mean tell you about the center of your data, measures of absolute dispersion tell you how how spread out your data is. The Dispersion (Absolute) Calculator provides several key statistics to help you understand the variability and consistency within your dataset. This is crucial in fields like quality control, finance (for risk assessment), and scientific research to understand the spread of measurements. To use the tool, enter your dataset into the text area, with numbers separated by either commas or spaces. The calculator is designed to handle your data entry flexibly. After you click 'Calculate', it will compute and display four important measures of absolute dispersion: 1. **Range:** This is the simplest measure of spread, calculated as the difference between the highest and lowest values in your dataset. It gives a quick sense of the total span of your data. 2. **Quartile Deviation:** Also known as the semi-interquartile range, this measures the spread of the middle 50% of your data. It is calculated as half the difference between the third quartile (Q3) and the first quartile (Q1). It is less sensitive to outliers than the range. 3. **Mean Deviation:** This is the average of the absolute differences between each data point and the mean of the dataset. It provides a straightforward measure of the average distance from the center. 4. **Standard Deviation:** This is the most common and statistically robust measure of dispersion. It calculates the square root of the variance and indicates how much the individual data points, on average, deviate from the mean. A low standard deviation means the data points are clustered closely around the mean, while a high standard deviation indicates they are spread out over a wider range.