SUMMARY
This discussion focuses on adjusting Amazon product ratings based on the number of reviews to provide a more accurate assessment of product quality. The user proposes using a Bayesian approach to calculate an adjusted rating, emphasizing the importance of a higher number of reviews for reliability. They also explore calculating confidence intervals using Excel's T-distribution and N-distribution functions for a 95% confidence level, seeking feedback on their methodology and potential alternatives.
PREREQUISITES
- Understanding of Bayesian statistics
- Familiarity with confidence intervals
- Proficiency in Excel functions, specifically T-distribution and N-distribution
- Basic knowledge of product rating systems
NEXT STEPS
- Research Bayesian statistics for rating adjustments
- Learn how to calculate confidence intervals in Excel
- Explore alternative statistical methods for product rating evaluation
- Investigate the impact of sample size on rating reliability
USEFUL FOR
Data analysts, e-commerce professionals, product managers, and anyone interested in improving the accuracy of product ratings based on review quantity.