market basket analysis

Modul ini membahas implementasi metode clustering K-Means, K-Median, Fuzzy C-Means, DBSCAN, dan Mean Shift pada dataset housing. Analisis dilakukan untuk mengelompokkan data berdasarkan kemiripan karakteristik properti serta mengevaluasi hasil clustering menggunakan metode Elbow dan Silhouette. Hasil menunjukkan bahwa K-Means memberikan pengelompokan yang relatif lebih stabil dibandingkan metode lainnya.

DAT301 HW3

An ioslides presentation explaining simple linear regression using the mtcars dataset, including the regression model, coefficient interpretation, ggplot visualizations, an interactive plotly graph, and a prediction example.

An introduction to hypothesis testing covering null and alternative hypotheses, the Z-test statistic, critical values, and p-values. Includes a full worked example, annotated normal distribution plots, and an interactive 3D surface showing how sample size and standard deviation affect the Z-statistic. Type I and Type II errors and statistical power are also discussed. All visualizations built in R using ggplot2 and plotly.

Introduction to simple linear regression with examples and visualization Statistical analysis of linear relationships using R