It takes a keen mind and a wealth of knowledge to data mine. The ability to extract data and analyze it has become increasingly sought after with the booming of information available to us. However, it could take years of studying to become a highly-skilled programmer. And yet, everyone starts somewhere. Linear Regression Using R: An Introduction to Data Modeling is a great place to start. The textbook speaks directly to readers as if it is a tutorial. This informal tone makes it simple for beginners to learn this challenging programming model using the R programming language.
The book offers fundamentals that will prepare students to continue in more challenging data modeling courses. It begins by introducing the topic and defining linear regression model and R. Then, it moves onto concepts that help students understand data. Next, the book explains one-factor and multi-factor regressions. Finally, it explores predicting responses and reading data. Plus, Linear Regression Using R: An Introduction to Data Modeling breaks information down in a step-by-step process. Therefore, readers can always refer back to it. The textbook comes with plenty of visuals, including tables, graphs, and coding examples. These parts all work together to enhance clarity for readers.
About the Author of Linear Regression Using R: An Introduction to Data Modeling
David J. Lilja holds a Ph.D. in electrical engineering from the University of Illinois at Urbana-Champaign. Currently, he is the Louis John Schnell Professor of Electrical and Computer Engineering at the University of Minnesota in Minneapolis. He was previously head of the college’s ECE department. He has also led and served on numerous conference program committees. The Institute of Electrical Engineering elected him a fellow, as well as distinguished visitor at its Computer Society. Lilja has also received several other recognition for his research in computer architecture, computer systems performance analysis, approximate computing, and more.