Applied Regression Analysis

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A01=Christer Thrane
Applied Regression Analysis
Author_Christer Thrane
categorical outcome modelling
Category=GPS
Category=JHBC
Category=KCH
Category=PBT
causal inference methods
Count Data Regression Models
Data Set
Dummy Variables
econometrics
eq_bestseller
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Exercise Hours
GPA
Grade Point Average
House Sale Prices
Iv Coefficient
Iv Probit
Iv Probit Estimate
Iv Probit Regression
Iv Regression
linear regression
LPM
model assumption testing
Multi-level Regression Models
Multinomial Logistic Regression
multiple regression
NB
NB Coefficient
non-linearity
Ordinal Regression Model
Panel Data Regression
Proportional Odds Assumption
Quantile Regression
quantitative data analysis
R
regression analysis for non-statisticians
regression model
Regression Models
Relevant Control Variables
research methods
Sample Regression Coefficient
significance testing
Smoking Status Variable
social science statistics
SPSS data interpretation
Stata
statistics
statistics programs
variables

Product details

  • ISBN 9781138335486
  • Weight: 900g
  • Dimensions: 156 x 234mm
  • Publication Date: 28 Oct 2019
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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This book is an introduction to regression analysis, focusing on the practicalities of doing regression analysis on real-life data.

Contrary to other textbooks on regression, this book is based on the idea that you do not necessarily need to know much about statistics and mathematics to get a firm grip on regression and perform it to perfection. This non-technical point of departure is complemented by practical examples of real-life data analysis using statistics software such as Stata, R and SPSS. Parts 1 and 2 of the book cover the basics, such as simple linear regression, multiple linear regression, how to interpret the output from statistics programs, significance testing and the key regression assumptions. Part 3 deals with how to practically handle violations of the classical linear regression assumptions, regression modeling for categorical y-variables and instrumental variable (IV) regression. Part 4 puts the various purposes of, or motivations for, regression into the wider context of writing a scholarly report and points to some extensions to related statistical techniques.

This book is written primarily for those who need to do regression analysis in practice, and not only to understand how this method works in theory. The book’s accessible approach is recommended for students from across the social sciences.

Christer Thrane holds a Ph.D. in Sociology and is Professor at Inland Norway University of Applied Sciences. His research interests include quantitative modeling studies in leisure, recreation, sports and tourism. He has 25 years of experience in teaching quantitative research methods and regression analysis.

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