Course Description
In this course, the concepts of multivariate statistics will be studied which include the basic concepts of multivariate statistics, matrices, vectors and their operations, as well as classification in multivariate statistics, the concept of normal multivariate distribution, hypothesis testing, the concept of MANOVA, the concept of Principle Component Analysis, Fuzzy and Structural Equation Modeling (SEM), clustering method. Apart from that, students are expected to be able to design problem solutions using techniques in multivariate statistics. Be able to explain the results of problem solving using techniques in multivariate statistics
Program Objectives (PO)
- Mahasiswa memahami konsep statistika multivariat, matriks, vektor, dan operasinya pada statistika multivariat
- Mahasiswa mampu memahami proses reduksi multivariat (PCA dan FA) dan menerapkannya pada problem riil
- Mahasiswa mampu memahami konsep klasterisasi multivariat dan menerapkannya pada problem riil
- Mahasiswa mampu memahami konsep pemodelan multivariat seperti Linear Model, GLM, SEM, dan PLS serta dapat menerapkannya pada problem riil
- Mahasiswa dapat mengimplementasikan analisis multivariat pada permasalahan nyata dan merealisasikan ide kreatif, serta memaparkan hasil analisis secara ilmiah