Accuracy Metrics and Decomposition

Fit GLM and GLMMs to create standardized CPUE indices that can be used as trends of relative biomass in stock assessments

Here I reviewed Kaitlan's original spatial analysis to compute the number of census tracts that fall within both limited and full purpose Austin (which spill into other counties). Towards the end, I also conducted an analysis of census tracts that we might consider excluding from the index due to very small % falling within the atx bounds.

Principal Component Analysis (PCA) is a fundamental technique for dimensionality reduction. This report applies PCA to a well-known wine dataset containing the chemical analysis of 13 constituents for wines derived from three different cultivars. The objective is to reduce the dimensionality of the data, visualize the underlying structure, and investigate whether the chemical profiles alone can distinguish the wine types.

Customer segmentation is a fundamental application of unsupervised learning in marketing analytics. This report employs the K-means clustering algorithm to segment customers of a retail mall based on demographic and behavioral variables—namely, age, annual income, and spending score. The objective is to derive actionable customer profiles to inform targeted marketing strategies.