The Interquartile Range (IQR) Calculator is an interactive and data-driven tool designed to help analysts, researchers, and decision-makers compute the IQR of a dataset. The IQR is a robust measure of variability that quantifies the spread of the middle 50% of the data, making it less sensitive to outliers compared to the range or standard deviation. This tool allows users to input numerical data and calculates the IQR along with the first quartile (Q1), second quartile (Q2, or median), and third quartile (Q3). It also visualizes the data distribution using boxplots for enhanced clarity.

Key Features:

1. Dynamic Input Fields: Users can input datasets with up to five variables or upload a CSV file containing their data.
2. IQR Calculation: Automatically compute Q1, Q2 (median), Q3, and the IQR for the dataset.
3. Interactive Charts: Visualize the dataset’s distribution using boxplots to highlight quartiles, outliers, and spread.
4. Scenario Testing: Allow users to adjust inputs dynamically to explore how changes in data affect the IQR.
5. PDF Export Functionality: Generate downloadable reports summarizing IQR 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.
• Educators calculating IQR for student performance metrics to assess variability.
• Data scientists assessing the robustness of statistical models by identifying extreme values.

How It Works:
Users input numerical data for up to five variables or upload a CSV file containing their data. The tool computes Q1, Q2 (median), Q3, and the IQR and displays the results in a table. Outcomes are visualized using interactive boxplots, allowing users to interpret the dataset’s distribution. Users can customize inputs dynamically, analyze scenarios, and download detailed reports in PDF format for further analysis or sharing with stakeholders.