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Conversion Significance for Signup Redesign

Easy

Statistics & Probability

Asked at 2 companies2Hypothesis TestingConfidence IntervalsP-Values

Also asked at

Problem

Business Context

StreamCart, a subscription video platform, changed its signup page to reduce friction and ran a randomized A/B test. The product manager wants to know whether the observed change in signup conversion is real or just sampling noise.

Problem Statement

Determine whether the treatment page produced a statistically significant change in conversion rate versus the control page using a two-proportion z-test.

Given Data

Group	Users Exposed	Conversions	Conversion Rate
Control (old signup page)	18,500	2,220	12.00%
Treatment (new signup page)	19,100	2,464	12.90%

Additional test settings:

Parameter	Value
Significance level	0.05
Test type	Two-tailed
Confidence level	95%

Requirements

State the null and alternative hypotheses.
Compute the sample conversion rates and the observed lift.
Calculate the pooled proportion and pooled standard error.
Compute the z-statistic and two-sided p-value.
Construct a 95% confidence interval for the difference in conversion rates.
Decide whether the change is statistically significant at the 5% level.
Briefly explain whether the result is large enough to matter for the business.

Assumptions

Users were randomly assigned to control and treatment.
Each user appears once in the analysis.
Conversion is binary and independent across users.
Sample sizes are large enough for the normal approximation to be valid.
No major instrumentation bugs or sample-ratio mismatch occurred during the test.

Sample Data

Example 1

Input

{"alpha":0.05,"control_n":18500,"treatment_n":19100,"control_rate":0.12,"treatment_rate":0.1290052356,"confidence_level":0.95,"control_conversions":2220,"treatment_conversions":2464}

Output(none)

Problem

Business Context

Problem Statement

Determine whether the treatment page produced a statistically significant change in conversion rate versus the control page using a two-proportion z-test.

Given Data

Group	Users Exposed	Conversions	Conversion Rate
Control (old signup page)	18,500	2,220	12.00%
Treatment (new signup page)	19,100	2,464	12.90%

Additional test settings:

Parameter	Value
Significance level	0.05
Test type	Two-tailed
Confidence level	95%

Requirements

State the null and alternative hypotheses.
Compute the sample conversion rates and the observed lift.
Calculate the pooled proportion and pooled standard error.
Compute the z-statistic and two-sided p-value.
Construct a 95% confidence interval for the difference in conversion rates.
Decide whether the change is statistically significant at the 5% level.
Briefly explain whether the result is large enough to matter for the business.

Assumptions

Users were randomly assigned to control and treatment.
Each user appears once in the analysis.
Conversion is binary and independent across users.
Sample sizes are large enough for the normal approximation to be valid.
No major instrumentation bugs or sample-ratio mismatch occurred during the test.

Sample Data

Example 1

Input

{"alpha":0.05,"control_n":18500,"treatment_n":19100,"control_rate":0.12,"treatment_rate":0.1290052356,"confidence_level":0.95,"control_conversions":2220,"treatment_conversions":2464}

Output(none)

Your answer

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Conversion Significance for Signup RedesignMedium Conversion Lift Significance for Signup RedesignMedium ASignificance Test for Signup ConversionEasy

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Conversion Significance for Signup Redesign

Easy

Statistics & Probability

Asked at 2 companies2Hypothesis TestingConfidence IntervalsP-Values

Also asked at

Problem

Business Context

Problem Statement

Determine whether the treatment page produced a statistically significant change in conversion rate versus the control page using a two-proportion z-test.

Given Data

Group	Users Exposed	Conversions	Conversion Rate
Control (old signup page)	18,500	2,220	12.00%
Treatment (new signup page)	19,100	2,464	12.90%

Additional test settings:

Parameter	Value
Significance level	0.05
Test type	Two-tailed
Confidence level	95%

Requirements

State the null and alternative hypotheses.
Compute the sample conversion rates and the observed lift.
Calculate the pooled proportion and pooled standard error.
Compute the z-statistic and two-sided p-value.
Construct a 95% confidence interval for the difference in conversion rates.
Decide whether the change is statistically significant at the 5% level.
Briefly explain whether the result is large enough to matter for the business.

Assumptions

Users were randomly assigned to control and treatment.
Each user appears once in the analysis.
Conversion is binary and independent across users.
Sample sizes are large enough for the normal approximation to be valid.
No major instrumentation bugs or sample-ratio mismatch occurred during the test.

Sample Data

Example 1

Input

{"alpha":0.05,"control_n":18500,"treatment_n":19100,"control_rate":0.12,"treatment_rate":0.1290052356,"confidence_level":0.95,"control_conversions":2220,"treatment_conversions":2464}

Output(none)

Problem

Business Context

Problem Statement

Determine whether the treatment page produced a statistically significant change in conversion rate versus the control page using a two-proportion z-test.

Given Data

Group	Users Exposed	Conversions	Conversion Rate
Control (old signup page)	18,500	2,220	12.00%
Treatment (new signup page)	19,100	2,464	12.90%

Additional test settings:

Parameter	Value
Significance level	0.05
Test type	Two-tailed
Confidence level	95%

Requirements

State the null and alternative hypotheses.
Compute the sample conversion rates and the observed lift.
Calculate the pooled proportion and pooled standard error.
Compute the z-statistic and two-sided p-value.
Construct a 95% confidence interval for the difference in conversion rates.
Decide whether the change is statistically significant at the 5% level.
Briefly explain whether the result is large enough to matter for the business.

Assumptions

Users were randomly assigned to control and treatment.
Each user appears once in the analysis.
Conversion is binary and independent across users.
Sample sizes are large enough for the normal approximation to be valid.
No major instrumentation bugs or sample-ratio mismatch occurred during the test.

Sample Data

Example 1

Input

{"alpha":0.05,"control_n":18500,"treatment_n":19100,"control_rate":0.12,"treatment_rate":0.1290052356,"confidence_level":0.95,"control_conversions":2220,"treatment_conversions":2464}

Output(none)

Your answer

Try one AI text evaluation on us

Get structured feedback, scored against a 4-axis rubric. Premium unlocks unlimited.

0 wordstarget ~200

Up next

Conversion Significance for Signup RedesignMedium Conversion Lift Significance for Signup RedesignMedium ASignificance Test for Signup ConversionEasy

Next question