Probability and Statistics for Science and Engineering with Examples in R, 2nd Edition

Probability and Statistics for Science and Engineering with Examples in R teaches students how to use R software to obtain summary statistics, calculate probabilities and quantiles, find confidence intervals, and conduct statistical testing.

The first chapter introduces methods for describing statistics. Over the course of the subsequent eight chapters students will learn about probability, discrete and continuous distributions, multiple random variables, point estimation and testing, and inferences based on one and two samples. The book features a comprehensive table for each type of test to help students choose appropriate statistical tests and confidence intervals.

Based on years of classroom experience and extensively class-tested, Probability and Statistics for Science and Engineering with Examples in R is designed for one-semester courses in probability and statistics, and specifically for students in the natural sciences or engineering. The material is also suitable for business and economics students who have studied calculus.

Hongshik Ahn holds a Ph.D. in statistics from the University of Wisconsin, Madison. Dr. Ahn is currently a professor in the Department of Applied Mathematics and Statistics at Stony Brook University. He worked at National Center for Toxicological Research, FDA before joining Stony Brook University. Recently he served as the vice president of SUNY Korea. His research interests include tree-structured regression and classification, bioinformatics, generalized linear modeling, and risk assessment. Dr. Ahn has been working on NIH grants on various biostatistical and medical researches. He has been published in three book chapters and over 60 peer-reviewed journals. Dr. Ahn also published a book entitled Mathematical Analysis of Genesis, from Shinil Books.

Table of Contents

Chapter 1- Describing Data
Chapter 2- Probability
Chapter 3- Discrete Distributions
Chapter 4- Continuous Distributions
Chapter 5- Multiple Random Variables
Chapter 6- Sampling Distributions
Chapter 7- Introduction To Point Estimation And Testing
Chapter 8- Inferences Based On One Sample
Chapter 9- Inferences Based On Two Samples