An R-based data visualization examining how role specialization and geography shape salaries across five data careers — Data Architect, Data Engineer, Data Scientist, Business Analyst, and Data Analyst — using BLS OEWS May 2024 state-level wage data.

Curso optativo-Biología-Universidad de Panamá

This document develops a deeper understanding of how to interpret multiple regression models. It focuses on: - testing individual predictors using t-tests - interpreting coefficients in the presence of other variables - understanding why variables may appear important on their own but not in a multiple model - comparing overall model fit using R^2 and adjusted R^2 - drawing meaningful conclusions from regression output The aim is to move from simply reading regression tables to understanding what the results imply about relationships in real data.

This document focuses on interpreting the results of multiple regression models. It covers: - hypothesis testing for individual coefficients using t-tests - interpreting p-values in a multivariate setting - understanding the difference between R^2 and adjusted R^2 - why predictors may lose significance in multiple regression - how to connect statistical results to meaningful conclusions The goal is to develop a clear understanding of what regression results do, and do not, tell us about relationships in data.

Derivation / proof of the Frechet Distributions Expected Value and Variance

Analysis of NOAA storm data to identify weather events most harmful to population health and economic consequences

Derivations of the Weibull Distribution Expected Value, Variance, and Moment Generating Functions.

Derivations of the Pareto Distribution's Expected Value and Variance