Causal inference: the Mixtape
Cunningham, Scott
Causal inference: the Mixtape - London: Yale University Press, 2021 - x, 572p. ; pb, 22 cm.
Includes index
An accessible and contemporary introduction to the methods for determining cause and effect in the social sciences Causal inference encompasses the tools that allow social scientists to determine what causes what. Economists--who generally can't run controlled experiments to test and validate their hypotheses--apply these tools to observational data to make connections. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied, whether the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the introduction of malaria nets in developing regions on economic growth. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and Stata programming languages
9780300251685
Causation
Social sciences--Data processing
Social sciences--Methodology
Dependence - Statistics
501 / CUN
Causal inference: the Mixtape - London: Yale University Press, 2021 - x, 572p. ; pb, 22 cm.
Includes index
An accessible and contemporary introduction to the methods for determining cause and effect in the social sciences Causal inference encompasses the tools that allow social scientists to determine what causes what. Economists--who generally can't run controlled experiments to test and validate their hypotheses--apply these tools to observational data to make connections. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied, whether the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the introduction of malaria nets in developing regions on economic growth. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and Stata programming languages
9780300251685
Causation
Social sciences--Data processing
Social sciences--Methodology
Dependence - Statistics
501 / CUN
