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The Language of Studies

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Title: The Language of Studies


1
The Language of Studies
  • Lecture 8
  • Secs. 3.1 3.3
  • Wed, Sep 14, 2005

2
Observation vs. Experimentation
  • Observational study A study in which the
    subjects are not manipulated or controlled in any
    way, but simply observed.
  • Designed experiment A study in which the
    researchers actively impose some treatment on the
    subjects and observe the response.

3
Think About It
  • Think About It, p. 147.

4
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?

5
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?

6
Explanatory and Response Variables
  • Response variable The variable that measures
    the outcome. It is believed to be affected by
    the explanatory variable.
  • Explanatory variable The variable or factor
    that is thought to explain the observed outcome.
    It is believed to affect the response variable.

7
Lets Do It!
  • Example 3.1, p. 149 Explanatory Variable and
    Response Variable.
  • Lets do it! 3.1, p. 151 Explanatory Variable
    versus Response Variable.
  • Lets do it! 3.2, p. 151 Food Myths.

8
Levels and Treatments
  • The explanatory variable is typically denoted X.
  • The response variable is typically denoted Y.
  • Values of the explanatory variable are called
    levels.
  • If there is more than one explanatory variable,
    then combinations of their values are called
    treatments.

9
Confound It!
  • Confounding variable A variable whose effect
    cannot be separated from the effect of the
    explanatory variable.
  • If a study has one or more confounding variables,
    then the researchers cannot attribute changes in
    the response variable to any one explanatory
    variable.
  • Normally, researchers try to control for all
    confounding variables (that they can think of).

10
Example
  • Example 3.4, p. 152 Treating Multiple Sclerosis
    with Protein.
  • Lets Do It! 3.3, p. 154 Invasive versus
    noninvasive Cancer Treatments.

11
Do Explanatory Variables Explain?
  • 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!
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