- descriptive statistics to characterize key metrics in the brewing process
- k-means clustering and derivative dynamic time warping to distinguish between good and bad batches
- multiple regression models to predict product volume loss during manufacturing
- and an ANOVA (analysis of variance) to determine if there was a statistically significant difference between percentage losses between products
04 November 2012
show me the numbers.
Why am I crazy about numbers? Well, it all started last year with my senior thesis. A group of us led by Dr. Nicole Radziwill had the opportunity to analyze the production data from Starr Hill Brewery and the goal was to improve the overall beer brewing process. By using R to play with the numbers, we were able to use:
Subscribe to:
Post Comments (Atom)
No comments:
Post a Comment