Regression Analysis

Regular price €52.99
A01=Jeremy Arkes
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Author_Jeremy Arkes
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bayesian
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Coefficient Estimates
data analysis
Dummy Variable
econometrics
empirical analysis
Empirical Relationship
eq_business-finance-law
eq_isMigrated=1
eq_isMigrated=2
eq_non-fiction
eq_society-politics
Estimating Peer Effects
Fixed Effects Group
Gdp Growth
Granger Causality Model
Hot Hand
Hot Hand Effect
Insignificant Coefficient Estimate
Key Explanatory Variable
Lagged Unemployment Rate
linear regression
Minimum Wage Increases
multivariate analysis
Negative Binomial
Non-normal Error Terms
OLS Method
p-values
regression analysis
Regression Discontinuity Models
research project
Self-selection Bias
Significant Coefficient Estimate
Standardized Coefficient Estimates
STATA
State Unemployment Rates
statistics
Time Series Variable
True Causal Effect
variables

Product details

  • ISBN 9781032257839
  • Weight: 712g
  • Dimensions: 174 x 246mm
  • Publication Date: 19 Jan 2023
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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This thoroughly practical and engaging textbook is designed to equip students with the skills needed to undertake sound regression analysis without requiring high-level math.

Regression Analysis covers the concepts needed to design optimal regression models and to properly interpret regressions. It details the most common pitfalls, including three sources of bias not covered in other textbooks. Rather than focusing on equations and proofs, the book develops an understanding of these biases visually and with examples of situations in which such biases could arise. In addition, it describes how ‘holding other factors constant’ actually works and when it does not work. This second edition features a new chapter on integrity and ethics, and has been updated throughout to include more international examples. Each chapter offers examples, exercises, and clear summaries, all of which are designed to support student learning to help towards producing responsible research.

This is the textbook the author wishes he had learned from, as it would have helped him avoid many research mistakes he made in his career. It is ideal for anyone learning quantitative methods in the social sciences, business, medicine, and data analytics. It will also appeal to researchers and academics looking to better understand regressions. Additional digital supplements are available at: www.youtube.com/channel/UCenm3BWqQyXA2JRKB_QXGyw.

Jeremy Arkes is a retired economics professor from the Graduate School of Business and Public Policy, Naval Postgraduate School, U.S.A. He is currently writing books on economics, nature, and basketball.