STAT1008 Lecture Notes - Lecture 4: Dependent And Independent Variables, Confounding
Experiments and Observational Studies
● Association and Causation:
○ Two variables are associated if values of one variable tend to be related to
values of the other variable
○ Two variables are causally associated if changing the value of the
explanatory variable influences the value of the response variable
○ ASSOCIATION IS NOT NECESSARILY CAUSAL
● Confounding Variable:
○ A third variable that is associated with both the explanatory variable and
the response variable is calling a confounding variable
○ A confounding variable can offer a plausible explanation for an association
between the explanatory and response variable
○ Whenever confounding variables are present (or may be present), a
causal association cannot be determined
○ Linked to response and explanatory variable e.g. wealth is the
confounding variable in the TV and life rate example
● Experiment vs Observational Study:
○ An observational study is a study in which the researcher does not actively
control the value of any variable, but simply observes the values as they
naturally exist
○ An experiment study is a study in which the researcher actively controls
one or more of the explanatory variables
● Observational Studies:
○ There are almost always confounding variables in observational studies
○ Observational studies can almost never be used to establish causation
● COMMON MISTAKE:
○ THE INVALID ASSUMPTION THAT CORRELATION (ASSOCIATION)
IMPLIES CAUSE IS PROBABLY AMONG THE TWO OR THREE MOST
SERIOUS AND COMMON ERRORS OF HUMAN REASONING
● Randomisation:
○ How can we make sure to avoid confounding variables? RANDOMLY
assign values of the explanatory variable
○ In a randomised experiment the explanatory variable for each unit is
determined randomly, before the response variable is measured
○ The different levels of the explanatory variable are known as treatments
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Document Summary
Two variables are associated if values of one variable tend to be related to values of the other variable. Two variables are causally associated if changing the value of the explanatory variable influences the value of the response variable. A third variable that is associated with both the explanatory variable and the response variable is calling a confounding variable. A confounding variable can offer a plausible explanation for an association between the explanatory and response variable. Whenever confounding variables are present (or may be present), a causal association cannot be determined. Linked to response and explanatory variable e. g. wealth is the confounding variable in the tv and life rate example. An observational study is a study in which the researcher does not actively control the value of any variable, but simply observes the values as they naturally exist. An experiment study is a study in which the researcher actively controls one or more of the explanatory variables.
