Regression Analysis is a major coursework for many research and statistics students. Although many know only about simple linear regression analysis, it actually expanded into non-linear regression analysis and multiple linear regression analysis as well. Non linear regression analysis is used for data sets which do not have a linear relationship and multiple linear regression analysis is used for data sets with more than one independent variable. Most importantly, residual tests in regression analysis are used to confirm the stability and reliability of the regression model. Residual tests are a crucial point in any regression analysis, that a student must have knowledge on.
Many students and researchers fail to analyze data sets properly due to lack of knowledge in all types of regression analysis. If you do not get desirable and fitting regression model, then it must be that another regression model should be used for the data set.
Furthermore, the books which are written on complex topics on regression analysis are not easy to understand. Identifying this shortage , writer has dedicated her time into writing a comprehensible book on regression analysis covering the topics related to
- Simple Linear Regression
- Residual Tests
- Non-Linear Regression
- Multiple linear regression
Even the complex calculations are presented step by step, in an uncomplicated manner. The examples are solved using manual calculations and statistical software such as Minitab and R (RStudio Version 4.0.0).
Concepts such as parameter testing, residual testing, ANOVA table, exponential regression models, quadratic regression models, partial F test, multi-collinearity , best subsets regression and step-wise regression are also explained with relevant examples.
“Introduction to Regression Analysis” is a basic but complete guide to regression analysis Even a beginner can easily self-study. Necessary commands and outputs are explicitly presented in each example
Interpreting outputs is one of the major struggles a student go through in his or her research work.
This book guides how to interpret regression analysis outputs properly
If you want to champion your knowledge on regression analysis, use this book.
I got a clear understanding on residual tests after reading this book. It immensely helped me in data modeling paper. The definitions mentioned in the book are very easy to remember. Moreover, it explains even about non-linear regression and multi-linear regression. This must be the only book that made me understand regression analysis very clearly. Other books were kind of complicated for me. In short, the book was very helpful and I 100% recommend it.
This is very good book.The book emphasizes the need for critical thinking in the analysis and how to identify the potential pitfalls in major research studies. The examples used in the book are relatable, relevant to current events, and referenced throughout the book for continuity.