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Simple regression and the U.S. Statistical Abstracts (2012) : infant mortality and poverty across the U.S.

This dataset example introduces simple regression, which allows researchers to evaluate whether a continuous dependent variable is a linear function of a single independent variable. The simple linear regression model is most commonly estimated via ordinary least squares (OLS), and is sometimes call...

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Bibliographic Details
Format: eBook
Language:English
Published: London SAGE Publications, 2015.
SAGE Publications Ltd.
Subjects:
Regression analysis.
Regression analysis > Case studies.
Research > Statistical methods.
Research > Statistical methods > Case studies.
Infants > Mortality > United States > Statistics.
Poverty > United States > Statistics.
Regression Analysis
Analyse de régression.
Analyse de régression > Études de cas.
Recherche > Méthodes statistiques.
Recherche > Méthodes statistiques > Études de cas.
Nourrissons > Mortalité > États-Unis > Statistiques.
Pauvreté > États-Unis > Statistiques.
Infants > Mortality
Poverty
Regression analysis
Research > Statistical methods
United States
Case studies
Statistics
Online Access:Connect to the full text of the electronic book
Description
Summary:This dataset example introduces simple regression, which allows researchers to evaluate whether a continuous dependent variable is a linear function of a single independent variable. The simple linear regression model is most commonly estimated via ordinary least squares (OLS), and is sometimes called OLS regression. This example uses a subset of data looking specifically at whether the poverty rate in a US state predicts a state's infant mortality rate. Analysis like this might help researchers and policy makers better understand the link between poverty and adverse health outcomes.
Physical Description:1 online resource : illustrations (black and white, and colour)
Audience:Specialized.
ISBN:1473947588
9781473947580