Full Description
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.
Contents
Preface
Acknowledgement
1. Data Analysis—Introduction
2. Basic R Language and MS Excel
3. Descriptive Statistics and Data Visualisation
4. Correlation and Regression Analysis
5. Probability and Probability Distribution
6. Sampling, Sampling Distribution, and Estimation of Parameters
7. Hypothesis Testing and Small Sampling Concepts
8. Analysis of Variance (ANOVA)
9. Chi-Square Test and Different Non-parametric Tests
10. Statistical Quality Control and Acceptance Sampling
11. Time Series Analysis
12. Statistical Decision Analysis
CD Contents
Excel Implementation and R Programs
Additional Topics
13. Cluster Analysis and Classification
14. Advanced Topics (Conjoint Analysis, Logistic Regression and Panel Data Analysis)
Bibliography
Index
