Looking for Book on Regression

In summary, regression analysis is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. There are several types of regression, including linear regression, logistic regression, polynomial regression, and multiple regression, each with its own assumptions and limitations. The choice of regression model depends on the type of data and research question, and it is commonly used in various fields for predictive modeling. However, it has limitations such as assuming a linear relationship and normally distributed data, which should be considered when interpreting the results.
  • #1
Jummeth
1
0
Hi,

I hope this is the correct section, I am looking for a good starting book about Parametric Regression and Regression Diagnostics.

I am currently slogging through "Semi-Parametric regression" Ruppert et-al (2003) and I'd like a slightly easier book that goes slightly more slowly and with more explanations on Linear Regression.

Thanks muchly in advance.
 
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  • #2
A standard book is Greene's "Econometric Analysis", or easier, "Econometric Methods" by Jonhston and DInardo.
I know those, unfortunately, they are quite expensive.
 
  • #3


Hi there,

Thank you for reaching out with your request for a book on regression. There are many great resources out there, so I'm sure you will find one that suits your needs. Here are a few suggestions for books on parametric regression and regression diagnostics:

1. "Introduction to Linear Regression Analysis" by Douglas C. Montgomery, Elizabeth A. Peck, and G. Geoffrey Vining. This book provides a comprehensive introduction to linear regression, including parametric and non-parametric methods, and covers regression diagnostics in detail.

2. "Applied Linear Statistical Models" by Michael H. Kutner, Christopher J. Nachtsheim, John Neter, and William Li. This book covers linear regression and its applications, including parametric and non-parametric methods, and also includes a section on regression diagnostics.

3. "Regression Analysis by Example" by Samprit Chatterjee and Ali S. Hadi. This book presents regression analysis in a practical and intuitive way, making it easier for beginners to understand. It also includes a chapter on regression diagnostics.

I hope these suggestions are helpful to you. Happy reading!
 

1. What is regression analysis?

Regression analysis is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. It is typically used to predict the value of the dependent variable based on the values of the independent variables.

2. What are the different types of regression?

There are several types of regression, including linear regression, logistic regression, polynomial regression, and multiple regression. Each type is used for different types of data and has its own assumptions and limitations.

3. How do I choose the right regression model for my data?

The choice of regression model depends on the type of data, the research question, and the assumptions of each model. It is important to evaluate the data and understand the underlying relationships before selecting a regression model.

4. What are some common applications of regression analysis?

Regression analysis is commonly used in fields such as economics, finance, psychology, and social sciences to analyze and predict relationships between variables. It is also used in machine learning and data mining for predictive modeling.

5. Are there any limitations to regression analysis?

Like any statistical technique, regression analysis has its limitations. It assumes a linear relationship between variables and may not be suitable for non-linear relationships. It also assumes that the data is normally distributed and free of outliers. It is important to understand these limitations when interpreting the results of a regression analysis.

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