TY  - BOOK
AU  - Kivedal, Bjørnar Karlsen
TI  - Applied statistics and econometrics: basic topics and tools with gretl and R
SN  - 9783031531415
U1  - 330.015195 
PY  - 2024///
CY  - Cham
PB  - Palgrave Macmillan
KW  - Econometric analysis
KW  - Econometrics
N1  - Table of contents:
Table of contents (10 chapters)
Front Matter
Pages i-xviii
Download chapter PDF 
Introduction
Bjørnar Karlsen Kivedal
Pages 1-3
Start Using Gretl and R
Bjørnar Karlsen Kivedal
Pages 5-18
Basic Material
Bjørnar Karlsen Kivedal
Pages 19-38
Hypothesis Testing
Bjørnar Karlsen Kivedal
Pages 39-57
Simple Linear Regression
Bjørnar Karlsen Kivedal
Pages 59-93
Multiple Regression
Bjørnar Karlsen Kivedal
Pages 95-123
Regression Using Dummy Variables
Bjørnar Karlsen Kivedal
Pages 125-155
Non-Linear Relationships
Bjørnar Karlsen Kivedal
Pages 157-176
Time Series Data
Bjørnar Karlsen Kivedal
Pages 177-223
Other Statistical Tools
Bjørnar Karlsen Kivedal
Pages 225-242
Back Matter
Pages 243-246

[https://link.springer.com/book/10.1007/978-3-031-53142-2]
N2  - This accessible textbook introduces the foundations of applied econometrics and statistics for undergraduate students. It covers key topics in econometrics by using step-by-step examples in Gretl and R, providing a guide to using statistical software and the tools for econometric analysis in one self-contained resource.

Taking a concise, non-technical approach, the book covers topics including simple regression and hypothesis testing, multiple regression with control variables and isolating effects, instrumental variables, dummy variables, non-linear effects, probability models, heteroskedasticity, time series analysis, and other applied statistical tools such as t-tests and chi squared tests. The book uses small data sets to easily facilitate students’ transition from manual statistical calculations to using and understanding statistical software, including step-by-step examples of regression analysis, as well as additional chapters to aid with econometric notation and mathematical prerequisites, and accompanying online exercises and data sets. This book will be a valuable resource for upper undergraduate students taking courses in introductory econometrics and statistics, as well as students in business administration and other fields of study in social sciences utilising quantitative methods. Graduate students may also benefit from the book
(https://link.springer.com/book/10.1007/978-3-031-53142-2)
ER  -