User 136 · Research · Groups · Tf038 Live Ttest
Executive Summary

Executive Summary

Key findings from the Welch independent-samples t-test comparing revenue between A/B variants

Mean Revenue A
42.85
Mean Revenue B
48.06
P-Value
0.0001
Cohen's d
-0.6415
T-Statistic
-3.9284
Sample Size A
75
Sample Size B
75
The difference in mean revenue between Variant A ($42.85) and Variant B ($48.06) is statistically significant (p = 0.000131). Cohen's d = -0.642, indicating a medium effect size. The 95% confidence interval for the mean difference is [-7.84, -2.59] USD.
Interpretation

The difference in mean revenue between Variant A ($42.85) and Variant B ($48.06) is statistically significant (p = 0.000131). Cohen's d = -0.642, indicating a medium effect size. The 95% confidence interval for the mean difference is [-7.84, -2.59] USD.

Data Table

Descriptive Statistics by Variant

Mean, standard deviation, sample size, and standard error of revenue per visitor for each experiment variant

VariantRevenue Usd
A42.85
B48.06
Interpretation

Variant A had a mean revenue of $42.85 (SD = $8.37, n = 75, SE = $0.9666). Variant B had a mean revenue of $48.06 (SD = $7.88, n = 75, SE = $0.9102). The absolute mean difference between groups is $5.22.

Data Table

T-Test Results and Effect Size

Welch t-statistic, degrees of freedom, p-value, confidence interval, and Cohen's d effect size

VariantRevenue Usd
T-Statistic-3.9284
Degrees of Freedom147.47
P-Value0.0001309
95% CI (Mean Diff)[-7.8397, -2.5921]
Cohen's d-0.6415
Effect SizeMedium
ResultSignificant
Interpretation

Welch's t-test yielded t(147.5) = -3.928, p = 0.000131. The 95% confidence interval for the mean difference runs from $-7.84 to $-2.59. Cohen's d = -0.642, representing a medium practical effect. The result is significant at α = 0.05.

Visualization

Revenue Distribution by Variant

Box plots comparing the revenue distribution shape, median, and outliers between A/B variants

Interpretation

The box plot reveals the spread and central tendency of revenue for each variant. Variant A has a median revenue of $42.35 while Variant B has a median of $47.62. Outliers, if present, are shown as individual points beyond the whiskers and may influence the group means seen in the t-test.

Visualization

Revenue Density Shape by Variant

Violin plots illustrating the distribution shape and density of revenue per visitor for each variant

Interpretation

Violin plots show the full probability density of revenue for each variant. A wider violin at a given revenue level indicates more visitors concentrated there. If the distributions appear roughly bell-shaped and symmetric, the normality assumption underlying the t-test is reasonably satisfied. Any skewness or multimodality should be noted as it may affect interpretation.

Visualization

Mean Revenue by Variant

Bar chart comparing mean revenue per visitor between control and treatment variants

Interpretation

The bar chart compares mean revenue per visitor across the two experiment variants. Variant B leads by $5.22 per visitor. This difference is significant (p = 0.000131). The effect size (Cohen's d = -0.642) is classified as medium.

Visualization

Revenue Distribution Overlay

Overlaid histograms of raw revenue values per visitor for each variant, supporting the normality assumption check

Interpretation

The overlaid histogram displays the raw revenue distribution for each variant, allowing visual inspection of normality and overlap. Welch's t-test is robust to moderate departures from normality when sample sizes are adequate. Substantial overlap between variants suggests a smaller practical effect, while well-separated distributions indicate a larger revenue difference.

Your data has more stories to tell. Run any analysis on your own data — 60+ validated R modules, interactive reports, AI insights, and PDF export. 2,000 free credits on signup.
Try Free — No Signup Sign Up Free

Report an Issue

Tell us what's wrong. You'll get a free re-run of this analysis so you can try again with different parameters. If the re-run still doesn't meet your expectations, we'll refund your credits.

Want to run this analysis on your own data? Upload CSV — Free Analysis See Pricing