Book contents
- Elementary Statistics for Public Administration
- Reviews
- Elementary Statistics for Public Administration
- Copyright page
- Contents
- Preface
- Acknowledgments
- To the Student
- Part 1
- Part 2
- Part 3
- Part 4
- 14 Bivariate Regression
- 15 Multivariate Regression
- 16 Regression Assumptions
- 17 Interactive Relationships and Interaction Terms in Regression
- 18 Logistic Regression
- Book part
- References
- Index
14 - Bivariate Regression
from Part 4
Published online by Cambridge University Press: 01 November 2024
- Elementary Statistics for Public Administration
- Reviews
- Elementary Statistics for Public Administration
- Copyright page
- Contents
- Preface
- Acknowledgments
- To the Student
- Part 1
- Part 2
- Part 3
- Part 4
- 14 Bivariate Regression
- 15 Multivariate Regression
- 16 Regression Assumptions
- 17 Interactive Relationships and Interaction Terms in Regression
- 18 Logistic Regression
- Book part
- References
- Index
Summary
This chapter is devoted to extensive instruction regarding bivariate regression, also known as ordinary least squares regression (OLS).Students are presented with a scatterplot of data with a best-fitting line drawn through it.They are instructed on how to calculate the equation of this line (least squares line) by hand and with the R Commander.Interpretation of the statistical output of the y-intercept, beta coefficient, and R-squared value are discussed.Statistical significance of the beta coefficient and its implications for the relationship between an independent and dependent variable are described.Finally, the use of the regression equation for prediction is illustrated.
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- Information
- Elementary Statistics for Public AdministrationAn Applied Perspective, pp. 271 - 298Publisher: Cambridge University PressPrint publication year: 2024