A/B Testing Conversion ANOVA

import matplotlib.pyplot as plt
import numpy as np
import scipy.stats as stats

np.random.seed(42)

# Conversion rates (%) for different page variants
control = np.random.normal(3.2, 0.8, 100)
variant_a = np.random.normal(3.8, 0.9, 100)
variant_b = np.random.normal(4.5, 1.0, 100)
variant_c = np.random.normal(4.1, 0.85, 100)

F_stat, p_value = stats.f_oneway(control, variant_a, variant_b, variant_c)

fig, ax = plt.subplots(figsize=(12, 7), facecolor='#0a0a0f')
ax.set_facecolor('#0a0a0f')

colors = ['#F5276C', '#27D3F5', '#6CF527', '#F5B027']
data = [control, variant_a, variant_b, variant_c]

bp = ax.boxplot(data, positions=[1, 2, 3, 4], widths=0.6, patch_artist=True,
                medianprops={'color': 'white', 'linewidth': 2},
                whiskerprops={'color': '#666666', 'linewidth': 1.5},
                capprops={'color': '#666666', 'linewidth': 1.5},
                flierprops={'marker': 'o', 'markerfacecolor': '#888888', 'markersize': 4, 'alpha': 0.5})

for patch, color in zip(bp['boxes'], colors):
    patch.set_facecolor(color)
    patch.set_alpha(0.7)
    patch.set_edgecolor('white')
    patch.set_linewidth(1.5)

# Add scatter points
for i, (d, color) in enumerate(zip(data, colors)):
    x = np.random.normal(i+1, 0.08, len(d))
    ax.scatter(x, d, c=color, alpha=0.4, s=15, zorder=1)

labels = ['Control', 'Variant A', 'Variant B', 'Variant C']
means = [d.mean() for d in data]

# Mean markers
for i, (mean, color) in enumerate(zip(means, colors)):
    ax.scatter([i+1], [mean], color='white', s=80, marker='D', zorder=5, edgecolors=color, linewidths=2)
    ax.text(i+1, 0.8, f'μ={mean:.2f}%', ha='center', fontsize=9, color=color, fontweight='bold')

# Stats header
stats_text = f"ANOVA: F={F_stat:.2f}, p={p_value:.4f} | Winner: Variant B (+{((variant_b.mean()-control.mean())/control.mean()*100):.1f}%)"
bbox = dict(boxstyle="round,pad=0.3", facecolor='#0d1117', edgecolor='#6CF527', lw=2)
ax.text(0.5, 1.02, stats_text, transform=ax.transAxes, fontsize=10, color='white',
        ha='center', va='bottom', fontfamily='monospace', bbox=bbox)

ax.set_xticks([1, 2, 3, 4])
ax.set_xticklabels(labels, fontsize=11, color='white')
ax.set_ylabel('Conversion Rate (%)', fontsize=12, color='white', fontweight='500')
ax.set_title('Landing Page A/B Test Results\nConversion Rate by Variant', 
             fontsize=14, color='white', fontweight='bold', pad=25)

ax.tick_params(colors='#888888')
for spine in ax.spines.values():
    spine.set_color('#333333')
ax.yaxis.grid(True, color='#1a1a2e', linewidth=0.5)
ax.set_axisbelow(True)
ax.set_ylim(0.5, 7.5)

plt.tight_layout()
plt.show()