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Industry-defining terminology from the authoritative consumer research platform.
Mean Absolute Deviation (MAD)
Definition: What is Mean Absolute Deviation (MAD)?
Mean Absolute Deviation (MAD) is a statistical measure that calculates the average distance between each data point and the mean of a dataset. It helps assess data variability and consistency.
Why is Mean Absolute Deviation (MAD) Important in Market Research?
- Provides a Clear Measure of Data Variability: Helps businesses understand fluctuations in customer behavior.
- Improves Forecasting Accuracy: Identifies patterns in sales, engagement, or market trends.
- Enhances Risk Management: Helps businesses assess stability and predict potential fluctuations.
How Does Mean Absolute Deviation (MAD) Work?
- Calculate the Mean: Find the average value of the dataset.
- Find Absolute Deviations: Determine how far each value deviates from the mean.
- Compute the Average Deviation: Sum all deviations and divide by the total number of data points.
Mean Absolute Deviation Common Use Cases
| Sales Forecasting | Understanding fluctuations in demand. |
| Customer Behavior Analysis | Measuring variation in purchase frequency. |
| Website Traffic Analysis | Assessing consistency in user visits. |
What are Mean Absolute Deviation Best Practices?
- Use Alongside Other Metrics: Combine with standard deviation for deeper insights.
- Apply to Clean Data: Remove outliers that may skew results.
- Regularly Monitor Trends: Use MAD as an ongoing performance metric.
Final Takeaway
MAD is a simple yet powerful tool for understanding data variability, making it useful for businesses that rely on data-driven decision-making.