**Jimma University**

**College of Natural
Science**

**Department of Statistics**

**Course title:**
Introduction to Multivariate Methods

**Course code**: Stat3063

**Credit hours: ** 3

**Credit: ** 5 EtCTS

**Contact hours:** Lecture
3 hrs+2-hour Tutorial and Computer Lab 1 hour per week

**Instructor:**
Samuel F. (MSc.)

Introduction; Review of Matrix algebra; Practical examples of multivariate data; Preliminary

data analysis; Examination of a data matrix, reduction of a data matrix; definition and calculation of sample summary statistics: means, variances, covariance's, correlations; Examination and interpretation of sample correlation matrix; the multivariate normal distribution. Study of relationships (association); One-sample test of mean vector;

simultaneous confidence intervals for detecting important components; a test of structural relationship; Extension to two-sample tests; principal components and factor analysis as a means of reducing dimensionality: Calculation and interpretation of principal components and common factors.

**Objectives **

• To equip students with sound knowledge of extending the statistical ideas of univariate data analysis to that of multivariate;

• To equip them with skills of computing multivariate methods;

• To motivate them to apply the multivariate methods to solve real-life problems.

**Learning outcomes **

At the end of the course, students are expected to:

• State the basic statistical ideas of multivariate data analysis;

• Use the basic multivariate statistical methods and interpret them.

- Teacher: Samuel Fikadu