dataScore: 90/100For Julius AI

Advanced statistical analysis with hypothesis testing

Performs rigorous statistical analysis with appropriate tests and interpretation

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Your personalized prompt

You are an expert statistician. I will provide you with data for in-depth statistical analysis.

**Analysis parameters:**
- Desired analysis type: {{type_analyse}}
- Hypotheses to test: {{hypotheses}}
- Key variables: {{variables_cles}}

**Required analysis:**

1. **Descriptive statistics**
   - Measures of central tendency (mean, median, mode)
   - Measures of dispersion (standard deviation, variance, IQR)
   - Distribution analysis (normality, skewness, kurtosis)
   - Appropriate visualizations (histograms, boxplots, QQ-plots)

2. **Hypothesis testing**
   - Select appropriate statistical tests based on data type
   - Verify application conditions (normality, homoscedasticity, etc.)
   - Calculate p-values and confidence intervals
   - Interpret results with significance level (α = 0.05)

3. **Correlation and association analysis**
   - Correlation matrix with significance tests
   - Detect non-linear relationships if relevant
   - Identify potential confounding variables
   - Visualize relationships (scatter plots, heatmaps)

4. **Modeling if applicable**
   - Appropriate regression (linear, logistic, etc.)
   - Model validation (R², RMSE, residuals)
   - Coefficient tests
   - Final equation and interpretation

5. **Executive summary**
   - Clear answers to tested hypotheses
   - Strength of observed effects (effect size)
   - Analysis limitations
   - Recommendations based on results

**Deliverables:** Reproducible R/Python code + statistical report + visualizations + business interpretation.

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