1st Edition
Statistical Practice for Data Science With Hands-On Illustrations Using R
Preface
Chapter 1: Useful Preliminaries
Chapter 2: Data Visualization
Chapter 3: Two Sample Inference
Chapter 4: Fixed Effects Analysis of Variance Models
Chapter 5: Linear Regression Analysis
Chapter 6: Linear Regression – More Topics
Chapter 7: Generalized Linear Models (GLIM)
Chapter 8: More on GLIM and Related Methods
Chapter 9: Some Extensions to ANOVA Models
Chapter 10: Models for Dependent Data
Bibliography
Index
Biography
Nalini Ravishanker is Professor in the Department of Statistics at the University of Connecticut (UConn), Storrs. She has a PhD in Statistics and Operations Research from the Stern School of Business, New York University, and a B.Sc. in Statistics from Presidency College, Madras, India. Her primary area of research is time series analysis with applications in several domains.
G. Asha is Senior Professor in the Department of Statistics at Cochin University of Science and Technology, Cochin, Kerala, India. She has a MPhil in Statistics from University of Kerala and Ph D in Statistics from Cochin University of Science and Technology, Cochin. Her primary area of research is life time data analysis.
Haim Bar Professor in the Department of Statistics at the University of Connecticut (UConn), Storrs. He has a PhD in Statistics from Cornell University, MSc in Computer Science from Yale University, and BSc in Mathematics from the Hebrew University. His areas of interest include high-dimensional models, and applications in genomics.
