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The Language of Studies. Lecture 8 Secs. 3.1 – 3.3 Fri, Sep 10, 2004. Observation vs. Experimentation. Observational study – A study in which the subjects are not manipulated or controlled in any way, but simply observed.

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the language of studies

The Language of Studies

Lecture 8

Secs. 3.1 – 3.3

Fri, Sep 10, 2004

observation vs experimentation
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.
think about it
Think About It
  • Think About It, p. 131.
  • Example – Charter School Achievement on the 2003 National Assessment of Educational Progress, page ii, 2ndparagraph.
explanatory and response variables
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.
let s do it
Let’s Do It!
  • Example 3.1, p. 132 – Explanatory Variable and Response Variable.
  • Let’s do it! 3.1, p. 134 – Explanatory Variable versus Response Variable.
  • Let’s do it! 3.2, p. 134 – Food Myths.
  • Example – Charter School Achievement on the 2003 National Assessment of Educational Progress, pages ii - iii.
levels and treatments
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.
example
Example
  • Example – Charter School Achievement on the 2003 National Assessment of Educational Progress, pages ii – iii.
confound it
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, the researchers did not properly control for the confounding variable.
example1
Example
  • Example 3.3, p. 135 – Treating Multiple Sclerosis with Protein.
  • Let’s Do It! 3.3, p. 136 – Invasive versus noninvasive Cancer Treatments.
  • Example – Charter School Achievement on the 2003 National Assessment of Educational Progress, page 3, last paragraph.
confounding variables
Confounding Variables

Location

Not

Cen. City

Cen. City

lower

lower

Afr.-Amer.

Minority

Status

Non

Afr.-Amer.

lower

higher

confounding variables1
Confounding Variables

Location

Not

Cen. City

Cen. City

lower

lower

Afr.-Amer.

lower

Minority

Status

Non

Afr.-Amer.

lower

higher

higher

lower

higher

control by minority status
Control by Minority Status

Minority Status

Non

Afr.-Amer.

Afr.-Amer.

lower

lower

Charter

lower

School

higher

higher

Public

higher

control by location
Control by Location

Location

Not

Cen. City

Cen. City

lower

lower

Charter

lower

Type of

School

higher

higher

Public

higher

do explanatory variables explain
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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