{% callout type="note" %}
For best practices, including tips on instrumentation, refer to [How to Analyze A/B Tests Results in Amplitude](/docs/get-started/analyze-a-b-test-results).
{% /callout %}

In Amplitude, A/B testing lets you compare the funnel conversion performance of two or more user segments against each other. View results as **improvement**, which describes the performance of a segment compared to the baseline, or as **statistical significance**, which shows the probability of observing a difference as extreme as what you saw, assuming the control and treatment have the same mean.

{% callout type="note" %}
For statistical significance calculations with continuous metrics, use the [experiment results chart](/docs/analytics/charts/experiment-results/experiment-results-dig-deeper) or the [Experiment end-to-end product](/docs/feature-experiment/overview).
{% /callout %}

By default, Amplitude uses the first segment added to the funnel analysis as the baseline. Change this in the _Baseline segment_ drop-down menu.

### A/B Test - Improvement

This chart displays the conversion rate for each segment across all steps in your funnel. You can have more than one variant in an A/B test, but you can only have one baseline.

### A/B Test - Significance

On this chart, a high value for a variant suggests it converts better than the baseline. A low value suggests it doesn't.

Amplitude considers the results statistically significant when the results meet these conditions:

- A sample size above 30 for both variants.
- Sample `size * conversion rate >= 5` **and** `sample size * (1-conversion rate) >= 5` for both variants.
- A significance of 95% or greater.

For more details, refer to [how Amplitude calculates statistical significance](/docs/feature-experiment/experiment-theory/analyze-with-t-test#common-questions).

### Understand the breakdown table

The data table below the chart breaks down the data. As with all data tables in Amplitude, you can export the data as a CSV file. The columns include:

- **Count:** The number of users or groups that entered the funnel.
- **Converted:** The number of users or groups that completed all the steps in the funnel with all conditions met.
- **% Conversion:** The number of converted users or groups, divided by the number of users or groups that entered the funnel.
- **% Improvement over Baseline:** Amplitude calculates this with the equation `(% conversion for that variant - % conversion for the baseline) / (% conversion for the baseline)`. The percentage in the data table is green when the value is a positive number.
- **Significance:** The likelihood that the performance displayed for each test variant is **actually** different from zero, and not due to random fluctuations in the data. The higher this value is, the more confident you can be in your results. More formally, this is `1 - p-value`.