Data visualization is an integral part of data analysis and presentation. This course will introduce you to creating interesting visualizations of different types of data, ranging from simple univariate and bivariate numerical and categorical data, to more complex multi-variable data. During this course, you will learn to use simple scatter, box, line plots, etc. as well as interactive graphs and maps. Most importantly, the course will teach you the ideal visualization tool to use in different contexts. The course will use the powerful graphic tools of the R programming language.
Assistant Professor, MDAE
Dr. Sandhya Krishnan has taught data analytics and R programming at various places across India, and to a wide range of audiences including undergraduate and graduate students, faculty and other professionals. She believes that interesting stories are hidden behind numbers and anyone with a flair for numbers and the right training in data analytics can unravel these stories and present them to the world. She holds a Ph.D. from the University of Amsterdam and an MA in Economics from the University of Mumbai.
Assistant Professor, Fergusson College
Dr. Ishita Ghoshal teaches Macroeconomics, Econometrics and Mathematical Economics and conducts workshops on research methods, computer applications for Economics, applied Econometrics with various software like R, EViews, STATA, etc. Her areas of interest are Macroeconomics, Applied Econometrics and International trade. She holds a Ph.D. in Economics from the Gokhale Institute of Politics and Economics.
Scatter plots, lines, steps, box plots, adding parameters to the basic plot function- creating legends, adding colors, grid lines, viewing multiple graphs in a single pane, etc.
Bar plots, histograms, pie charts, quintiles, Percentiles, Q-Q plots, function curves
Basic line graphs, scatters, regression lines, balloon plots, etc. with ggplot2
Bar plots, correlation matrix, functions, network graphs
Heat maps, 3-dimensional and animated graphics
Chloreopath maps and creating maps from a shape file
MDAE alumni working in diverse roles across leading companies.
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