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Checkout System Time Reduction Analysis
Comparing checkout times between old and new systems using Welch's t-test for difference in means. Shows 95% CI for time reduction with effect size (Cohen's d), statistical significance testing, and business impact calculations for deployment decision.
Input
What you provide to the skill
New checkout (n=180, mean=4.2 min, SD=1.8) vs old (n=165, mean=5.1 min, SD=2.1). Calculate 95% CI for time difference.
Output
What the skill generates for you
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CHECKOUT TIME REDUCTION ANALYSIS
Old Checkout System:
• Sample size: 165
• Mean time: 5.10 minutes
• Standard deviation: 2.10 minutes
New Checkout System:
• Sample size: 180
• Mean time: 4.20 minutes
• Standard deviation: 1.80 minutes
Time Reduction (Old - New):
• Point estimate: 0.90 minutes
• Standard error: 0.2115 minutes
• 95% Confidence Interval: (0.48, 1.32) minutes
Statistical Significance Test:
• t-statistic: 4.256
• Degrees of freedom: 324.5
• P-value: 0.000027
• Cohen’s d (effect size): 0.462
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INTERPRETATION
The new checkout system reduces checkout time by an average of 0.90 minutes compared to the old system.
95% Confidence Interval: (0.48, 1.32) minutes
We are 95% confident that the true average time reduction for all customers falls between 0.48 and 1.32 minutes.
Statistical Significance:
• The difference is highly statistically significant (p < 0.001)
Effect Size:
• Cohen’s d = 0.462 (small effect)
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BUSINESS IMPLICATIONS
• Time Reduction: 0.90 minutes (17.6% improvement)
• The confidence interval does not include zero, confirming a real reduction
Practical Impact (assuming 1,000 daily customers):
• Daily time saved: 900 minutes (15.0 hours)
• Weekly time saved: 105 hours
• Annual time saved: 5,475 hours (684 work days)
Worst-Case Scenario (lower CI bound: 0.48 min):
• Even at the conservative estimate, customers save 0.48 minutes each
• Daily impact: 8.1 hours saved
Best-Case Scenario (upper CI bound: 1.32 min):
• Potential maximum benefit is 1.32 minutes per customer
• Daily impact: 21.9 hours saved
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RECOMMENDATION
The new checkout system demonstrates a statistically significant and practically meaningful reduction in checkout time. The small effect size (d = 0.46) combined with the narrow confidence interval indicates a reliable improvement.
✓ RECOMMENDATION: Deploy the new checkout system
Key Benefits:
• Proven time savings of 0.90 minutes per transaction
• Improved customer experience through faster checkout
• Increased capacity to serve more customers
• Statistical confidence in the improvement (p < 0.001)
Next Steps:
- Roll out new system to all customers
- Monitor checkout times to validate continued performance
- Track customer satisfaction metrics alongside time savings
- Quantify revenue impact from reduced cart abandonment
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About This Skill
Calculate and interpret confidence intervals for means, proportions, and group differences with visualizations and plain-language explanations for business decisions.
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