Data Analysis Using Statistics and Probability with R Language is a complete introduction to data analysis. It provides a sound understanding of the foundations of the data analysis, in addition to covering many important advanced topics. Moreover, all the techniques have been implemented using R language as well as Excel. This book is intended for the undergraduate and postgraduate students of Management and Engineering disciplines. It is also useful for research scholars. KEY FEATURES 1. Covers data analysis topics such as: • Descriptive statistics like mean, median, mode, standard deviation, skewness, kurtosis, correlation and regression • Probability and probability distribution • Inferential statistics like estimation of parameters, hypothesis testing, ANOVA test, chi-square and t-test • Statistical quality control, time series analysis, statistical decision theory • Explorative data analysis like clustering and classification • Advanced techniques like conjoint analysis, panel data analysis, and logistic regression analysis 2. Comprises 12 chapters which include examples, solved problems, review questions and unsolved problems. 3. Requires no programming background and can be used to understand theoretical concepts also by skipping programming. 4. R and Excel implementations, and additional advanced topics are available at https://phindia.com/partha_sarathi_ bishnu_ and_vandana_bhattacherjee 5. Whenever in any branch, data analysis technique is required, this book is the best. TARGET AUDIENCE • Students of MBA, ME/M.Tech, and BE/B.Tech. • M.Sc. (Computer Science), MCA, BCA, and research scholars
Data Analysis Using Statistics and Probability with R Language is a complete introduction to data analysis. It provides a sound understanding of the foundations of the data analysis, in addition to covering many important advanced topics. Moreover, all the techniques have been implemented using R language as well as Excel. This book is intended for the undergraduate and postgraduate students of Management and Engineering disciplines. It is also useful for research scholars. KEY FEATURES 1. Covers data analysis topics such as: • Descriptive statistics like mean, median, mode, standard deviation, skewness, kurtosis, correlation and regression • Probability and probability distribution • Inferential statistics like estimation of parameters, hypothesis testing, ANOVA test, chi-square and t-test • Statistical quality control, time series analysis, statistical decision theory • Explorative data analysis like clustering and classification • Advanced techniques like conjoint analysis, panel data analysis, and logistic regression analysis 2. Comprises 12 chapters which include examples, solved problems, review questions and unsolved problems. 3. Requires no programming background and can be used to understand theoretical concepts also by skipping programming. 4. R and Excel implementations, and additional advanced topics are available at https://phindia.com/partha_sarathi_ bishnu_ and_vandana_bhattacherjee 5. Whenever in any branch, data analysis technique is required, this book is the best. TARGET AUDIENCE • Students of MBA, ME/M.Tech, and BE/B.Tech. • M.Sc. (Computer Science), MCA, BCA, and research scholars
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