Log Transformation Calculator
Visualize and transform your data using logarithms.
Data Input
Enter your data points as comma-separated values. For example: 2, 10, 50, 250, 1000.
Default base is 10.
Transformed Data
Visualization
Understanding Log Transformation
Log transformation is a technique used to reduce skewness and make data more normal distribution-like. It is particularly useful when dealing with data that has a right-skewed distribution, meaning a long tail on the right side. By applying a logarithm to each data point, it compresses the range of large values and stretches the range of small values, thus normalizing the data. Common applications include finance, biology, and image processing. For example, in finance, stock prices or income data often benefit from log transformation.
- Formula: y' = logb(y), where y is the original data, b is the base of the logarithm, and y' is the transformed data.
- Common Bases: Base 10 (common logarithm), base e (natural logarithm), and base 2 (binary logarithm).
- Use Cases: Variance stabilization, handling skewed data, linearizing exponential relationships.
Learn more about log transformation on Wikipedia.