The Median Absolute Deviation (MAD) Calculator is an interactive and data-driven tool designed to help analysts, researchers, and decision-makers compute the MAD of a dataset. The MAD is a robust measure of variability that quantifies the spread of data around the median. It is particularly useful for datasets with outliers or non-normal distributions, as it is less sensitive to extreme values compared to standard deviation. This tool allows users to input numerical data and calculates the MAD along with other descriptive statistics.

Key Features:

1. Dynamic Input Fields: Users can input datasets with up to five variables or upload a CSV file containing their data.
2. MAD Calculation: Automatically compute the MAD and related metrics such as median, interquartile range (IQR), and robust z-scores.
3. Interactive Charts: Visualize the distribution of the data using histograms or boxplots to identify outliers and assess variability.
4. Scenario Testing: Allow users to adjust inputs dynamically to explore how changes in data affect the MAD.
5. PDF Export Functionality: Generate downloadable reports summarizing MAD results for presentations or sharing with stakeholders.
6. Modern and Stylish Design: A sleek interface with vibrant colors, animations, and clear typography to enhance user engagement.
7. Fully Responsive: Optimized for all devices, ensuring seamless functionality on desktops, tablets, and mobiles.
8. Self-Contained Container: The tool operates within its own container, ensuring no interference with the page header or footer.

Use Cases:

• Researchers analyzing the variability of experimental data with potential outliers.
• Data scientists assessing the robustness of statistical models by identifying extreme values.
• Academics teaching robust measures of variability and their applications in statistics.

How It Works:
Users input numerical data for up to five variables or upload a CSV file containing their data. The tool computes the MAD, median, IQR, and robust z-scores. Results are displayed in tables and visualizations, allowing users to interpret the variability of the data. Users can customize inputs dynamically, analyze scenarios, and download detailed reports in PDF format for further analysis or sharing with stakeholders.