Exploratory Data Analysis for Data Science with R Software (English)

ABOUT THE COURSE:Any data analysis requires statistical tools. The course describes the basic statistical tools and related concepts used in the exploratory data analysis. The use of analytical and graphical tools in data science will be explained. Their implementation using open-source R software will be demonstrated with the related software commands along with the interpretation of the outcomes of analytical and graphical tools.INTENDED AUDIENCE: All UG students in Mathematics, Engineering, ManagementPREREQUISITES: Mathematics background up to class 10 is needed. Having some preliminary knowledge will be helpful but not necessarily mandatoryINDUSTRY SUPPORT: All analytical companies and industries involved in mathematical and statistical computations, programming and simulations and having R & D set up will use this course

Syllabus

Week 1: Introduction to various topics and commands in R software
Week 2: Basic concepts of exploratory statistical data analysis, frequency and frequency distribution, cumulative distribution functions and their use with R software
Week 3: Graphical procedures with various graphs in one, two and three dimensions
Week 4: Graphical procedures with various graphs with ggplot2 package
Week 5: Measures of central tendency and their use with R software
Week 6: Measures of variation and their use with R software
Week 7: Moments, skewness, kurtosis and their use with R software
Week 8: Association of variables through graphics
Week 9: Association of continuous variables, various correlation coefficients and their use with R software
Association of discrete variables and their use with R software
Week 10: Fitting of linear models and their use with R software
Week 11: Selection of samples and simple random sampling
Week 12: Multivariate exploratory data analysis tools