Using EDA, ANOVA and Regression ot Optimise some Microbiology Data

Abstract

Bacteria are cultured in medical laboratories to identify them so patients can be treated correctly. The tryptone dataset contains measurements of bacteria counts following the culturing of five strains of Staphylococcus aureus. It also contains the time of incubation, temperature of incubation and concentration of tryptone, a nutrient. The question is whether the conditions recommended in the protocols for the culturing of these strains are optimal. The task is to find the incubation time, temperature and tryptone concentration that optimises the growth of this bacterium. Students may explore these data at several levels. Graphical methods can be used to investigate the relationship between the variables. ANOVA can be used with one-way, two-way and factorial models with interactions, to identify significant factors. Multiple polynomial regression methods can be used to model the data, with optimal conditions estimated by partial differentiation.

• Analysis of variance
• Exploratory data analysis
• Interactions
• Multiple regression
• Optimisation
• Outlier
• Polynomial regression.