Welch's t-test Tool

Means tool

Compare means of two independent groups with fan charts and narrative insights.

TEST OVERVIEW & EQUATIONS

The Welch t-test evaluates whether two independent group means differ when variances may be unequal.

Test statistic: $$t = \frac{\bar{x}_1 - \bar{x}_2 - \Delta_0}{\sqrt{\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2}}}$$

Confidence interval: $$(\bar{x}_1 - \bar{x}_2) \pm t_{\alpha/2,\,\nu} \sqrt{\frac{s_1^2}{n_1} + \frac{s_2^2}{n_2}}$$

Additional Notes

As degrees of freedom increase, Welch's t behaves like a z-test. When samples are small or variances highly imbalanced, keep the heavier tails in mind and report the estimated power.

MARKETING SCENARIOS

You're leading a marketing analytics project for an e-commerce brand that is A/B testing email campaigns. Group 1 might represent subscribers who received an optimized subject line, while Group 2 saw the current control subject line. After the campaign, you collected key performance indicators such as click-through rate, average order value, or downstream revenue per recipient.

Use the tool below to plug in the sample statistics for each variant, evaluate whether the observed lift is meaningful, and decide if the new creative warrants a broader rollout. Adjust the hypothesized difference to model the minimum effect size that would justify marketing spend.

INPUTS & SETTINGS

Select Data Entry / Upload Mode

Enter aggregated statistics for each group. Scenarios and uploads overwrite these fields automatically.

Group Name Mean (μ) Std. deviation (s) Sample size (n)
Group 1
Group 2

Upload summary inputs

Provide a CSV/TSV with exactly two rows, including columns such as group,mean,sd,n. Add optional delta0 and alpha columns to set the hypothesized difference and confidence level along with the stats.

Drag & drop summary file

Two groups required. Each row should describe one group.

No summary file uploaded.

Upload raw data

Upload a long-format file with columns like group,value. We’ll calculate the means, standard deviations, and sample sizes for the first two groups discovered.

Drag & Drop raw data file (.csv, .tsv, .txt)

Long format with headers like group,value; at least two unique groups. Up to 2,000 rows.

No raw file uploaded.

Analysis Settings

VISUAL OUTPUT

Means Fan Chart

Difference Fan Chart

Visual Output Settings

Means Fan Chart

Difference Fan Chart

Axis Mode

TEST RESULTS

APA-Style Statistical Reporting

Managerial Interpretation

Summary of Estimates

Measure Estimate Standard Error Lower Bound Upper Bound

DIAGNOSTICS & ASSUMPTIONS

Diagnostics & Assumption Tests

Provide group summaries to review sample size balance, variance ratios, power, and interval diagnostics.