Week 10 analysis using logistic regression to predict whether homes achieve premium quality ratings (8-10 out of 10). Models probability using living area, year built, garage size, and central air. Interprets coefficients as odds ratios, constructs confidence intervals using standard errors, and evaluates model performance with confusion matrix and accuracy metrics.

This report analyzes a nationwide georeferenced dataset compiled by the National Malaria Eradication Service (SENEPA). It contains 20,619 records of disease vectors (Phlebotominae, Triatominae, and Culicidae) collected between 1998 and 2023. The objective is to provide a reproducible and interactive tool for public health decision-making, allowing the exploration of spatial and temporal records of vectors associated with Dengue, Chagas, Malaria, Leishmaniasis, and Yellow Fever in Paraguay.

Penyelesaian tugas mandiri mata kuliah Pengantar Model Linear. Laporan ini berisi analisis regresi linear berganda menggunakan OLS berbasis matriks untuk memprediksi nilai ujian, lengkap dengan perhitungan Uji-F, Uji-t, R-squared manual, dan validasinya menggunakan fungsi bawaan lm() di R.

Razan Nur Muhammad Ihsan (3338240032)

Week 9 revised analysis building multiple regression model with living area, quality rating, and central air variables. Includes comprehensive diagnostics using the 5 plots from class: residuals vs fitted, residuals vs X values, correlation heatmap, residual histogram, and Q-Q plot. Evaluates linearity, normality, homoscedasticity, and multicollinearity with severity assessments and confidence levels for each assumption.