|
Activity Number:
|
509
|
|
Type:
|
Topic Contributed
|
|
Date/Time:
|
Wednesday, August 5, 2009 : 2:00 PM to 3:50 PM
|
|
Sponsor:
|
Section on Statistical Education
|
| Abstract - #305071 |
|
Title:
|
Distinguishing Association from Causation in Titles of News Stories
|
|
Author(s):
|
Robert Raymond*+ and Milo Schield
|
|
Companies:
|
University St. Thomas and W.M. Keck Statistical Literacy Project
|
|
Address:
|
800 Grandview, Roseville, MN, 55113,
|
|
Keywords:
|
statistical literacy
|
|
Abstract:
|
Headlines from 2,000 news stories were analyzed for the presence of 727 keywords indicating an association, a causal connection or something in-between. 71% had such keywords. Of those with such keywords, very few (6%) had keywords clearly indicating causation or association. Most (94%) had "between" keywords: keywords that described an association but had a causal connotation. Between keywords included action verb keywords such as ups or cuts (61%), comparison keywords such as more or less (19%), sufficient keywords such as prevent or stop (8%) and temporal or quasi-causal keywords such as after and due to (7%). A content analysis of three statistics textbooks indicates that statisticians may use effect without implying causation. This data may be useful for both statisticians and journalists in trying to understand how the other group distinguishes association from causation.
|
- The address information is for the authors that have a + after their name.
- Authors who are presenting talks have a * after their name.
Back to the full JSM 2009 program |
