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Statistical Data Analysis Using R: A Practical Introduction de Deepa Tyagi

Statistical Data Analysis Using R: A Practical Introduction

Autor Deepa Tyagi, Shalini Chandra, Shrawan Kumar
en Limba Engleză Hardback – 3 feb 2027
This book introduces statistical data analysis using R programming, covering tools such as descriptive statistics, regression, ANOVA, and nonparametric tests. It covers essential statistical tools, including descriptive statistics, probability distributions, and hypothesis testing, with practical examples and solved exercises. It introduces both built-in library packages and manual coding solutions, offering flexibility and clarity for learners. With numerous tables, diagrams, and hands-on programming exercises, this book makes R for statistical analysis easy to understand and master.
  • Comprehensive coverage of statistical tools, including descriptive statistics, regression, ANOVA, and nonparametric tests.
  • Includes a dual programming approach, built-in library packages, and manual coding solutions.
  • Focuses on graphics and data visualization for effective interpretation of results.
  • Practical R code examples and solved exercises for hands-on learning.
It is ideal is for undergraduate and postgraduate students, researchers, and professionals in fields such as statistics, computer science, business analytics, public health, psychology, economics, and environmental science.
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Trimite

Specificații

ISBN-13: 9781041307716
ISBN-10: 1041307713
Pagini: 296
Ilustrații: 168
Dimensiuni: 156 x 234 mm
Ediția:1
Editura: CRC Press
Colecția Chapman and Hall/CRC

Public țintă

Undergraduate Advanced

Cuprins

1. Introduction and Preliminaries. 2. Descriptive Statistics and Graphics. 3. Probability Distributions. 4. One-Sample and Two-Sample Tests. 5. Regression and Correlation. 6. Analysis of Variance, Analysis of Covariance, and the Kruskal-Wallis Test. 7. Multiple Linear Regression. 8. Logistic Regression and Generalized Linear Models. 9. Stepwise Regression Analysis.

Notă biografică

Deepa Tyagi is an assistant professor in the Department of Statistics at Shaheed Rajguru College of Applied Sciences for Women, Delhi University, East Delhi, India. Her research interests include regression analysis, time series analysis, and econometrics. She is a strong research professional with a doctorate (Ph.D.) in statistics and a Master of Philosophy (M.Phil.) in mathematical science from Banasthali University, Rajasthan, and gained her B.Sc. and M.Sc. degrees from Chaudhary Charan Singh University, Meerut, Uttar Pradesh.
With experience as a research associate at ICAR-Indian Agricultural Statistics Research Institute (IASRI), Sample Survey Division, PUSA, New Delhi, and as a junior research fellow (JRF) under the Department of Science and Technology (DST) project at the Centre for Mathematical Sciences (CMS), Banasthali University, Rajasthan, she has published numerous research articles in her field. She has expertise in various statistical and mathematical software tools, including EViews, SPSS, R, MATLAB, Mathematica, LaTeX, and Python.

Shalini Chandra has been working as a professor and HOD in the Department of Mathematics and Statistics at Banasthali University, Rajasthan, India, for over 20 years –with one year of teaching at the Indian Statistical Institute, North East Centre, Tezpur – since 2002.  She completed her undergraduate B.Sc. and postgraduate M.Sc. degrees at Lucknow University, Uttar Pradesh, and pursued her doctorate (Ph.D.) at M.D. University, Rohtak. She also has experience as a visiting scientist and associate professor at the Indian Statistical Institute, North East Centre, Tezpur.
Her research interests include regression analysis, time series analysis, biostatistics, and econometrics, and she has collaborated with national and international academic institutions, including NIT Durgapur, ISI Kolkata, IIT Delhi, and Concordia University, Canada. With expertise in statistical data analysis and mathematical software tools, including SPSS, MATLAB, EViews, C/C++, R software, LaTeX, and Python, she has published numerous articles and book chapters in her areas of interest.

Shrawan Kumar has been a professor in the Department of Statistics at Kirori Mal College, University of Delhi, New Delhi, India, since 1994. He completed his undergraduate degree  –a B.A. (Hons) in mathematical statistics, and a postgraduate degree – an M.A. in statistics –at Hindu College, Delhi University, and gained his doctorate (Ph.D.) and M.Phil. in statistics from the Department of Statistics at the University of Delhi.
His research interests include sampling distributions, statistical inference, reliability, and biostatistics and he has published numerous research articles in his areas of interest. His expertise lies in statistical data analysis software and tools, including Microsoft Office, SPSS, C/C++, and R.

Descriere

This book introduces statistical data analysis using R programming, covering tools like descriptive statistics, regression, ANOVA, and non-parametric tests. It covers essential statistical tools, including descriptive statistics, probability distributions, and hypothesis testing, with practical examples and solved exercises.