Data Transformer Math

📊 Data Transformer Pro Box-Cox Exponential Kurtosis Normality

Professional data transformation with skewness, kurtosis analysis, and normality assessment

📊 Box-Cox Transformation

📈 Exponential Transform

🔄 Log & Power

📉 Kurtosis Analysis

⚡ Normality Testing

📝

Data Input

λ (Lambda) Parameter: 0.5

Power (p): 2

📊

Statistical Analysis

📈 Original Data Statistics
N: --
Mean: --
Median: --
Std Dev: --
Skewness: --
Kurtosis: --
Distribution: --
Min: --
Max: --

🔄 Transformed Data Statistics
N: --
Mean: --
Median: --
Std Dev: --
Skewness: --
Kurtosis: --
Distribution: --
Min: --
Max: --

📋 Transformed Values (first 20):
--

📈

Distribution Comparison

📊

Normality Assessment

📊 Normality & Kurtosis Analysis
Original Skewness: --
Transformed Skewness: --
Original Kurtosis: --
Transformed Kurtosis: --
Improvement: --
Recommendation: --

📚

Transformation & Kurtosis Guide

📊 Box-Cox Transformation
y(λ) = (y^λ - 1)/λ (for λ ≠ 0)
y(λ) = ln(y) (for λ = 0)
Best for: Normalizing skewed data, stabilizing variance

📈 Kurtosis Interpretation
• Kurtosis = 3: Mesokurtic (Normal)
• Kurtosis > 3: Leptokurtic (Heavy tails)
• Kurtosis < 3: Platykurtic (Light tails)
• Excess Kurtosis = Kurtosis - 3

🔲 Log & Power Transforms
• Log: Reduces right skewness
• Square root: For count data
• Power: Flexible transformation

💡

When to Use

✅ Choose Box-Cox when:
• Data is positive
• Need to normalize distribution
• Want optimal λ parameter
• Preparing for parametric tests

📖 Kurtosis Guide:
• > 3: Heavy tails (outlier-prone)
• = 3: Normal distribution
• < 3: Light tails (uniform-like)
• Goal: Transform towards 3

⚠️ Cautions:
• Data must be positive for Box-Cox
• Transformations change interpretation
• Always check both skewness & kurtosis

📊 Data Transformer Pro — Box-Cox, Exponential, Log, Power transforms with skewness & kurtosis analysis

Data Transformer Pro — Professional data transformation tool with kurtosis analysis, normality testing, and multiple transformation methods.