Data Science using R is designed to cover majority of the capabilities of R from Analytics & Data Science perspective, which includes the following:

Learn about the basic statistics, including measures of central tendency, dispersion, skewness, kurtosis, graphical representation, probability, probability distribution, etc.

Learn about scatter diagram, correlation coefficient, confidence interval, Z distribution & t distribution, which are all required for Linear Regression understanding

Learn about the usage of R for building Regression models

Learn about the K-Means clustering algorithm & how to use R to accomplish the same

Learn about the science behind text mining, word cloud, sentiment analysis & accomplish the same using R

Learn about Forecasting models including AR, MA, ES, ARMA, ARIMA, etc., and how to accomplish the same using R

Learn about Logistic Regression & how to accomplish the same using R

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