Hanging Rootogram Chart for Power BI

Hanging Rootogram by Office Solution

The Hanging Rootogram chart by Office Solution is a specialized type of bar chart used in statistical analysis to compare observed data with expected data from a theoretical distribution, such as the normal distribution. In this chart, bars are "hung" from the axis representing the expected values, and their lengths indicate the difference between the square roots of the observed and expected frequencies. This visualization technique stabilizes variance and makes it easier to detect and interpret deviations between the observed data and the expected theoretical model, providing a clear visual assessment of the goodness-of-fit.

Key Benefits

Basic Features:

• Visual Clarity: Easily distinguish between observed and expected frequencies with hanging bars, providing an immediate visual representation of deviations.
• Compact Layout: A hanging design ensures a more compact and space-efficient display compared to traditional histograms.
• Dynamic Data Handling: Capable of managing large datasets with ease, ensuring smooth performance and quick rendering.
• License: No license support.

Premium Features:

• Customizable Thresholds: Set specific thresholds to highlight significant deviations between observed and expected data.
• Customizable Dimensions: The chart dimensions can be adjusted to fit various screen sizes and layouts, ensuring flexibility and adaptability.
• Interactive Elements: Hover over bars to get detailed tooltips that provide precise values and additional insights.
• Scalable Bar Height: Adjust the height of the bars with respect to the normal distribution curve of expected values or absolute values of the expected values.
• Bar Color-Coded: Use color coding to instantly identify the bars.
• Both Curves: The Both curve chart displays two lines, one for observed data and another for expected data, allowing for direct comparison.
• Area Between Curves: The shaded area between the observed and expected lines highlights discrepancies, making it easier to identify significant deviations.

Business Use Cases:

• Quality Control Teams: Use the Hanging Rootogram to compare defect rates against expected distributions, aiding in quality control and process improvement. Monitor compliance data to ensure adherence to regulatory standards by identifying significant deviations from expected values.
• Data Scientists & Statisticians: Validate statistical models by comparing observed data with theoretical distributions, ensuring model accuracy and reliability. Identify and analyze anomalies or outliers in datasets, enhancing the quality and integrity of data analysis.
• Marketing and Customer Analytics: Analyze customer behavior, such as purchase frequency or product preferences. By visualizing deviations from expected customer actions, marketers can tailor their strategies to better meet customer needs and preferences.
• Healthcare and Medical Research: Utilize hanging rootograms to analyze the distribution of health outcomes or medical test results. By visually representing deviations from expected outcomes, healthcare professionals and researchers can identify patterns, trends, and potential areas for further investigation or intervention.
• Supply Chain Management: Analyze the distribution of inventory levels, production lead times, or delivery delays in supply chain operations. By visually representing deviations from expected performance metrics, supply chain managers can identify bottlenecks, inefficiencies, and opportunities for optimization.

Note:

For more information, visit our website: https://innovationalofficesolution.com

Read this Hanging Rootogram documentation: https://innovationalofficesolution.com/Custom-Charts/hanging-rootogram-chart-2

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