Introduction to Statistics and Data Analysis

Part I Descriptive Statistics: Introduction and Framework.- Frequency Measures and Graphical Representation of Data.- Measures of Central Tendency and Dispersion.- Association of Two Variables.- Part I Probability Calculus: Combinatorics.- Elements of Probability Theory.- Random Variables.- Probability Distributions.- Part III Inductive Statistics: Inference.- Hypothesis Testing.- Linear Regression.- Part IV Appendices: Introduction to R .- Solutions to Exercises.- Technical Appendix.- Visual Summaries.

Dr. Christian Heumann is a professor at the Ludwig-Maximilian-Universität Munich, where he teaches students in Bachelor and Master programs offered by the Department of Statistics, as well as undergraduate students in the Bachelor of Science programs in business administration and economics. His research interests include statistical modeling, computational statistics and all aspects of missing data.

Dr. Michael Schomaker is a Senior Researcher and Biostatistician at the Centre For Infectious Disease Epidemiology & Research (CIDER), University of Cape Town, South Africa. He received his doctoral degree from the University of Munich. He has taught undergraduate students from the business and medical sciences for many years and has written contributions for various introductory textbooks. His research chiefly focuses on missing data, causal inference, model averaging and HIV/AIDS.

Dr. Shalabh is a Professor at the Indian Institute of Technology Kanpur (India). He received his Ph.D. from the University of Lucknow (India) and completed his post-doctoral work at the University of Pittsburgh (USA) and University of Munich (Germany). He has over twenty years experience in teaching and research. His main research areas are linear models, regression analysis, econometrics, error-measurement models, missing data models and sampling theory.