*Quan Li*

- Published in print:
- 2018
- Published Online:
- March 2019
- ISBN:
- 9780190656218
- eISBN:
- 9780190656256
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780190656218.003.0005
- Subject:
- Political Science, Political Theory

This chapter teaches how to use R to conduct regression analysis to answer the question: Does trade promote economic growth? It demonstrates how to specify a statistical model from a theoretical ...
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This chapter teaches how to use R to conduct regression analysis to answer the question: Does trade promote economic growth? It demonstrates how to specify a statistical model from a theoretical argument, prepare data, estimate and interpret the statistical model, and use the estimated results to make inferences and answer the question of interest. More specifically, it discusses the logic of regression analysis, the relationship between population and sample regression models, how to estimate a regression model in theory and practice, the estimation of sample regression model using OLS (ordinary least squares), the interpretation of estimation results, the statistical inference in regression analysis using hypothesis testing and confidence interval, the types of sum of squares and overall model fit, and how to report the model results. The validity of regression analysis is contingent upon the assumptions of the Gauss-Markov theorem being met.Less

This chapter teaches how to use R to conduct regression analysis to answer the question: Does trade promote economic growth? It demonstrates how to specify a statistical model from a theoretical argument, prepare data, estimate and interpret the statistical model, and use the estimated results to make inferences and answer the question of interest. More specifically, it discusses the logic of regression analysis, the relationship between population and sample regression models, how to estimate a regression model in theory and practice, the estimation of sample regression model using OLS (ordinary least squares), the interpretation of estimation results, the statistical inference in regression analysis using hypothesis testing and confidence interval, the types of sum of squares and overall model fit, and how to report the model results. The validity of regression analysis is contingent upon the assumptions of the Gauss-Markov theorem being met.

*Frank A. Cowell*

- Published in print:
- 2011
- Published Online:
- April 2015
- ISBN:
- 9780199594030
- eISBN:
- 9780191808654
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/acprof:osobl/9780199594030.003.0002
- Subject:
- Economics and Finance, Macro- and Monetary Economics

This chapter considers several standard inequality measurement tools that determine inequality in a large heterogeneous group of people. It describes these tools as methods of appraising information ...
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This chapter considers several standard inequality measurement tools that determine inequality in a large heterogeneous group of people. It describes these tools as methods of appraising information contained in an income distribution. It groups these tools under three broad headings: diagrams, inequality measures, and rankings. Under diagrams, the chapter enumerates four ways of representing inequality in pictures: Parade of Dwarfs, Frequency distribution, Lorenz curve, and log transformation. It lists down six conventional inequality measures: Range R, Relative mean deviation M, Variance V, Coefficient of variation c, Gini coefficient G, and Log variance v. It considers two ways of looking at inequality that may lead to ambiguous results: quantities and shares.Less

This chapter considers several standard inequality measurement tools that determine inequality in a large heterogeneous group of people. It describes these tools as methods of appraising information contained in an income distribution. It groups these tools under three broad headings: diagrams, inequality measures, and rankings. Under diagrams, the chapter enumerates four ways of representing inequality in pictures: Parade of Dwarfs, Frequency distribution, Lorenz curve, and log transformation. It lists down six conventional inequality measures: Range *R*, Relative mean deviation *M*, Variance *V*, Coefficient of variation *c*, Gini coefficient *G*, and Log variance *v*. It considers two ways of looking at inequality that may lead to ambiguous results: quantities and shares.

*Andrew Gelman and Deborah Nolan*

- Published in print:
- 2017
- Published Online:
- September 2017
- ISBN:
- 9780198785699
- eISBN:
- 9780191827518
- Item type:
- chapter

- Publisher:
- Oxford University Press
- DOI:
- 10.1093/oso/9780198785699.003.0005
- Subject:
- Mathematics, Educational Mathematics

This chapter addresses the descriptive treatment of linear regression with a single predictor: straight-line fitting, interpretation of the regression line and standard deviation, the confusing ...
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This chapter addresses the descriptive treatment of linear regression with a single predictor: straight-line fitting, interpretation of the regression line and standard deviation, the confusing phenomenon of “regression to the mean,” correlation, and conducting regressions on the computer. These concepts are illustrated with student discussions and activities. Many examples are of the sort commonly found in statistics textbooks, but the focus here is on how to work the examples into student-participation activities rather than simply examples to be read or shown on the blackboard. Topics include the following relationships: height and income, height and hand span, world population over time, and exam scores.Less

This chapter addresses the descriptive treatment of linear regression with a single predictor: straight-line fitting, interpretation of the regression line and standard deviation, the confusing phenomenon of “regression to the mean,” correlation, and conducting regressions on the computer. These concepts are illustrated with student discussions and activities. Many examples are of the sort commonly found in statistics textbooks, but the focus here is on how to work the examples into student-participation activities rather than simply examples to be read or shown on the blackboard. Topics include the following relationships: height and income, height and hand span, world population over time, and exam scores.