Regression Analysis in R

Regular price €198.40
A01=Jocelyn E. Bolin
advanced regression techniques in R
ANOVA
Author_Jocelyn E. Bolin
Bootstrapped Confidence Intervals
Category=JHBC
Category=PBT
causality
Cognitive Test Anxiety
College GPA
Dummy Coded
Dummy Variable
Durbin Watson Test
eq_bestseller
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
eq_society-politics
Forward Regression
HLM
Inferential Statistical Procedure
Kendall Tau
Linear models
mediation analysis
moderation effects
multilevel modeling
Multiple Linear Regression
Multiple Regression Framework
Negative Relationship
Nested Regression Models
Non-linear Term
OLS Regression
quantitative research methods
R program
Random Intercept
Regression Discontinuity Designs
Regression Model
Residual Standard Error
SAT Math
social science statistics
Spearman Rho
Spearman's Rank Correlation Rho
statistical inference
Verbal SAT
Vice Versa

Product details

  • ISBN 9781032257754
  • Weight: 421g
  • Dimensions: 156 x 234mm
  • Publication Date: 27 Jul 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Hardback
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Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid framework from which to expand into more complicated regression models. Concepts are demonstrated using R software and real data examples.

Key Features:

  • Full output examples complete with interpretation
  • Full syntax examples to help teach R code
  • Appendix explaining basic R functions
  • Methods for multilevel data that are often included in basic regression texts
  • End of Chapter Comprehension Exercises

Jocelyn E. Bolin is professor in the Department of Educational Psychology at Ball State University, where she teaches courses on introductory and intermediate statistics, multiple regression analysis, and multilevel modeling to graduate students in social science disciplines. She earned a PhD in educational psychology from Indiana University Bloomington. Her research interests include statistical methods for classification and clustering and use of multilevel modeling in the social sciences.