About the Course
Multivariate data analysis (MDA) is a tool to locate patterns and relationships between variables concurrently and it predicts the effect of a change in one/more variable/s on the other variable/s. It involves observation and analysis of more than one variable at a time and their responses. The researchers, engineers and practitioners often face a difficulty that how to handle data when the response is influenced by more than one variable.
Nowadays, MDA plays a significant role in data analysis as computational power grows dramatically and has wide range of applications in the field of consumer and market research, quality control and quality assurance, process optimization and process control, and research and development in engineering and social science. Further, MDA techniques provide a powerful test of significance compared to univariate techniques.
Name Of Organiser
Guru Nanak Dev Engineering College, Ludhiana, Punjab, India
- Introduction to MDA, Basic Matrix Algebra, Probability and Statistics
- Data Collection, Basics of Design of Experiments (Taguchi Method, RSM etc.)
- Data Mining, Multiple Regression, Regression Diagnostics and Model Adequacy, Binary and Multinomial Logistic Regression
- Analysis of Variance (ANOVA) and MANOVA
- Principal Component Analysis, Factor Analysis, Discriminant Analysis and Cluster Analysis
- Structural Equation Modeling (SEM) using AMOS
- Multi Objective Optimization, Significance of Weights of Importance (AHP and Entropy Weights method etc.)
- Multi Attribute Decision Making (SAW, WPM, WASPAS, TOPSIS etc.)
The course has the objective of introducing the participants with diverse strategies of managing multivariate data. MDA include an ability to glean a more realistic picture than looking at a single variable. At the end of the course, participants will be able to understand, apply and analyze:
- Fundamental concepts, principles of MDA and various techniques.
- Suitable statistical method associated with MDA.
- Appropriate statistical software like Minitab, Excel Sheet, AMOS and SPSS etc. for MDA.
- Decision making strategies in the presence of multivariate data.
The participants will be exposed to expert lectures on the logic and the theory behind the various techniques of MDA such as multivariate hypothesis testing, dimensionality reduction, latent structure discovery and clustering etc. along with multi attribute or multi objective decision making strategies. The hands on practice will be provided on statistical software like Minitab, SPSS, SYSTAT, Design Expert, Excel Sheet, Quality Companion and AMOS etc. through practice sessions in the laboratory.
There is no registration fee for the course. Completed registration form along with 1-page write-up (reasons to attend this course) should be sent by Email to:
Please send a single email with attachments as:
(a) The 1-page write-up and
(b) scanned copy of the filled-in and signed form.
The title of the email should be “AICTE Sponsored FDP on Multivariate Data Analysis”. Incomplete application forms will not be entertained.
Note: Bring duly signed original Registration Form at the time of registration in person if not submitted through post.
- Faculty Members (AICTE/UGC/MHRD)
- Research Scholars
- Industry Professionals
- R&D Persons
Personal laptops during the expert lectures and practice sessions will be allowed.
- Deadline for submitting Application: 20 Nov, 2019 (Scanned copy via Email only)
- Notification of Acceptance: 30 Nov, 2019
- Course Dates: 11– 24 Dec., 2019′
Seminar Hall, Mechanical Engineering Department, GNDEC, Ludhiana
As per AICTE mandatory requirement a course evaluation test (CET) will be conducted. The certificate will be issued to those participants who successfully attend and qualify CET.
Prof. (Dr.) Harwinder Singh
email@example.com; +91 98151-88044
Dr. Raman Kumar
firstname.lastname@example.org; +91 98551-00530
Prof. (Dr.) Harwinder Singh; FDP-MDA
Department of Mechanical Engineering,
Guru Nanak Dev Engineering College, Ludhiana, Punjab – 141006
Click here for the brochure and here for the official website.