The Language of Studies Lecture 10 Secs. 3.1 – 3.3 Fri, Sep 7, 2007

Observational study Experiment Response variable Explanatory variable Observation vs. Experimentation

An observational study does not manipulate the explanatory variables. An experiment does manipulate the explanatory variables.

Examples Which ones are observational and which are experiments?  Case Study 1: Empathy for cheaters  Case Study 4: Alcohol-related traffic deaths up in Virginia

Observation vs. Experimentation If an experimental study gives the researchers more control over the explanatory variables, then why would anyone conduct an observational study?

Example Suppose researchers wish to determine whether there is a relationship between cocaine usage by pregnant women and birth defects. Should this be an observational study or a designed experiment? Why?

Example A traffic engineer is studying a particular intersection to determine the traffic flow. He needs to know the average number of cars that turn left, turn right, and go straight. Should this be an observational study of a designed experiment? Why?

Levels and Treatments Values of the explanatory variable are called levels. If there is more than one explanatory variable, then combinations of their values are called treatments.

Confounding Variables. Confounding variable – A variable whose effect on the response variables cannot be separated from the effect of the explanatory variables. If a study has one or more confounding variables, then the researchers cannot attribute changes in the response variables to any one explanatory variable.

Case Study 6 Not Now, Dear. I Don’t Have a Headache In this study,  Identify the response variable(s).  Identify the explanatory variable(s).  Identify the levels or treatments. Can you think of any confounding variables?

Case Study 5 Food buying habits of people who buy wine or beer: cross sectional study Food buying habits of people who buy wine or beer: cross sectional study In this study,  Identify the response variable(s).  Identify the explanatory variable(s).  Identify the levels or treatments. Can you think of any confounding variables?

A study cannot prove that variations in the explanatory variable really were the cause of variations in the response variable. The study can only give evidence supporting that belief. It may be the case that there is a third variable that is affecting both the explanatory and response variables. It may be conceivable that the “response” variable affected the “explanatory” variable! Do “Explanatory” Variables Really Explain?

Evidence of Causation The following are evidence (but not proof) of causation.  The same association between the explanatory and response variables occurs in a variety of situations.  There is a plausible explanation of how the explanatory variable could affect the response variable.  There is no equally plausible third factor that could be affecting both the explanatory and the response variables.