Belajar software Rstudio

Built a dataset of 156 countries by merging World Bank and Our World in Data indicators, then used multiple linear regression in R to test whether tourism intensity predicts GDP per capita and national poverty rates. Log-transformed skewed variables and validated the models with residual plots, Q-Q plots, Cook’s distance, and VIF. Tourism intensity was a significant predictor in both models (R² = 0.72 for GDP, 0.59 for poverty). The weaker poverty result suggests tourism-driven growth doesn’t fully reach residents.

Using the mtcars dataset in R, this interactive presentation explores elementary linear regression techniques. This presentation investigates the relationship between vehicle weight and fuel efficiency (MPG) using data visualizations built with ggplot2, an interactive Plotly graph, regression analysis, model assumptions, and forecasts.

Belajar software RStudio

Tugas 2

¿Confiamos en las instituciones que toman decisiones globales y apoyamos la acción climática? Este análisis estadístico estudia la confianza y el apoyo de 100 personas hacia la gobernanza global, y pone a prueba afirmaciones como si la mayoría respalda las iniciativas climáticas o si la confianza cambia según la participación en espacios internacionales. Taller 3 de Estadística Inferencial, Grupo 5.