This shows the output of Exploratory Factor Analysis (EFA) functions from the package rwf. EFA uncovers the latent structure underlying a set of observed variables: it identifies groups of variables that share common variance, which are interpreted as factors. The functions include loading plots, scree plots, loading tables, residual diagnostics, and a full EFA report.

This shows the output of correlation functions from the package rwf. The functions include a correlation heatmap plotter, power analysis for correlation tests, a full bivariate correlation report (r, p, CI, adjusted p and sample size, all as lower-triangle matrices), and special correlation types for dichotomous and ordinal data (tetrachoric, polychoric, biserial, polyserial).

This shows the output of ANOVA-related functions from the package rwf. The functions cover non-parametric alternatives (Kruskal-Wallis), one-way and factorial ANOVA, MANOVA, effect size estimation, and post hoc comparisons. Each section shows rwf output alongside equivalent results from established packages so you can verify the numbers.

This shows the output of useful functions for training and testing from the package rwf. The functions include plotting ROC curves, confusion matrices, separability plots, and evaluating confusion matrix performance at different cut-off points. Additionally, it demonstrates k-fold and k-sample cross-validation procedures, scaling data, and calculating confusion matrix statistics.

HERBERT VALEM 240611010033

Sankey_CRem

Perbandingan dilakukan pada 5 sheet pengacakan pada 1 dataset yakni dataset Combined Cycle Power Plant menggunakan model selection AICc dan Cross Validation.

Tugas Pendalaman Materi SocMed Insights

Rida Inayah Rizkyah_333726_D26

followed teacher's instruction carefully