Regression and Regression Analysis
Bibliographic Data
| ID | 7076408 |
|---|---|
| Authors | Andrew M Lindner (0000-0003-4347-8787, Skidmore College), R Larson (0000-0002-2349-7510, University of Minnesota), Ryan P Larson |
| Year | 2018 |
| Pages | 1-2 |
| Publication date | 2018-04-27 |
| Open Access | Yes |
| Type | OTHER |
| Venue | The Blackwell Encyclopedia of Sociology (JOURNAL) |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1002/9781405165518.wbeosr041.pub2 |
| OpenAlex | W2990539259 |
| ISBN | 9781405165518 |
| Language | EN |
| References cited | 1 |
Regression is among the most common statistical techniques used to analyze correlational data. By controlling for intercorrelated variables, researchers attempt to isolate the effect of independent variables on a dependent variable. Due to limitations in ordinary least squares (OLS) regression, quantitative researchers use various extensions that allow for the analysis of more complex forms of data
Cross-sectional regression · Econometrics · Linear regression · Ordinary least squares · Partial least squares regression · Polynomial regression · Regression · Regression analysis · Regression diagnostic · Segmented regression · Statistical analysis · Statistics · Variable (mathematics · Variables · Advanced Statistical Methods and Models · Computer Science · Mathematics
| Highly cited | No |
|---|