ABOUT THE COURSE:Multivariate Procedures with R is designed to equip the learners with the necessary theory and application of multivariate procedures in academic, research, and business domains with appropriate examples. The comprehensive content is designed to manually compute various multivariate statistics for learning and R-based computations for application.INTENDED AUDIENCE: UG students of Science and Engineering. Students of Science, management, Engineering with basic mathematical background can do it. Working professionals in analytics and statistical computations, simulations and data analysis can also do it.PREREQUISITES: Mathematics background up to class 12 is needed. Having some preliminary knowledge will be helpful but not necessarily mandatory.INDUSTRY SUPPORT: All industries involved in mathematical and statistical computations, programming and simulations and having R & D set up will use this course.
Overview
Syllabus
Week 1: Basic fundamentals, Introduction to working in R, Brief introduction to commnds in R, data editing, R Studio, use of R as a calculator.Week 2:Calculations with Data Vector, Built in function, Matrix operations, Univariate statistical measures for central tendency and variations. Week 3:Handling bivariate data, Missing data handling, Measuring central tendency and variation with missing data Week 4:Introduction of coefficient of variation, Data frames, Box Plots, and Plots for discrete and continuous data.Week 5:Two and three-dimensional plots for univariate, bivariate and multivariate data, univariate, bivariate and multivariate random variables, univariate normal distributionWeek 6:Bivariate and multivariate normal distribution, Sampling distributionsWeek 7:Regression analysis, scaling of variablesWeek 8:Scaling of variablesWeek 9:Principle component analysisWeek 10:Discriminant analysisWeek 11:Canonical correlation analysisWeek 12:Cluster analysis
Taught by
Prof. Shalabh
