Chapter 7 Glossary

**ex**** post facto research: **when
a researcher goes back, after the research has been completed, looking to test hypotheses
that were not formulated prior to the beginning of the study. (p.232)

**archival**** data: **data from existing
records and public archives. (p. 234)

**instrumentation**** bias: **apparent
changes in participants that are really due to changes in the measuring instrument.
A real problem in archival research because the way records are kept may change
over time. For example, unemployment statistics are difficult to interpret
because the government has changed its definition of unemployment. (p. 238)

**content**** analysis: **a way to categorize
a wide range of open-ended (unrestricted) responses. Content analysis schemes
have been used to code the frequency of violence on certain television shows
and are often used to code archival data.

(p. 236)

**nonreactive****:
**measurements that are taken without changing the participantŐs behavior.
Researchers in both participant and naturalistic observation try to be nonreactive, but both often fail. (p. 239)

**participant**** observation: **an observation
procedure in which the observer participates with those being observed. The
observer becomes "one of them." Some worry that, in participant observation,
the observer may change the behavior of the people being observed. (p. 241)

**naturalistic**** observation: **a technique
of observing events as they occur in their natural setting--without
participating in those events. Advocates believe that naturalistic observation
has more external validity than lab observation. In addition, they hope that
naturalistic observation will be less reactive than either participant
observation or lab observation. (p. 241)

**scatterplot****:
**a graph made by plotting the scores of individuals on two variables (for
instance, plotting each participant's height and weight). By looking at this
graph, you should get an idea of what kind of correlation (positive, negative,
zero) exists between the two variables. (p. 253)

**positive**** correlation: **a relationship
between two variables in which the two variables tend to change in the same
direction--when one increases, the other tends to increase. (For example, height
and weight: The taller one is, the more one tends to
weigh; the less tall one is, the less one tends to weigh.) (p. 253)

**negative correlation: **a relationship between two variables
in which the two variables tend to change in opposite directions--when one is
high or increases, the other tends to below or decrease. An example of this
inverse relationship between two variables would be happiness and depression:
The more happy one is, the less depressed one is. (p.
255)

**zero**** correlation: **when there
does not appear to be a linear relationship between two variables. For practical
purposes, any correlation between -.10 and +.10 is often considered so small as to be essentially zero. (p. 255)

**illusory**** correlation: **when there
is really no relationship (a zero correlation) between two variables, but people
perceive that the variables are related. (p. 231)

**correlation**** coefficient: **a number
that can vary from -1.00 to +1.00. The sign of the correlation coefficient
indicates the kind of relationship that exists between two variables (positive
or negative/inversely related). The correlation coefficient also indicates the strength of the
relationship. Specifically, the closer the correlation coefficient is to 0, the
weaker the relationship; the farther from 0 (regardless of whether the
correlation is positive or negative), the
stronger the relationship. (p. 260)

**coefficient**** of determination: **the
square of the correlation coefficient; tells the degree to which knowing one variable
helps to know another. Can range from 0 (knowing a participant's score on one
variable tells you absolutely nothing about the participant's score on the
second variable) to 1.00 (knowing a participant's score on one variable tells
you exactly what the participant's score on the second variable was). Note that
the sign of the correlation coefficient has absolutely no effect on the coefficient of determination
(e.g, a -1 and a +1 correlation coefficient both have a coefficient of
determination of 1). (p. 260)

**restriction**** of range**: a problem
caused by when participants studied only represent a narrow range of scores on
a key variable. Restriction of range is a problem because to observe a sizable
correlation between two variables, both must be allowed to vary widely (if one
variable does not vary, the variables cannot vary together). Occasionally,
investigators fail to find a relationship between variables because they study
one or both variables only over a highly restricted range. For example, saying
that weight has nothing to do with playing offensive line in the NFL on the
basis of your finding that great offensive tackles do not weigh much more than
poor offensive tackles. Problem: You only compared people who ranged in weight
from 315 to 330 pounds. (p. 267)

**median****: **if you arrange all the
scores from lowest to highest, the middle score will be the median. (p.246)

**median**** split: **the procedure of
dividing participants into two groups (usually "low scorers" and "high scorers") based on whether
they score above or below the median (the middle score). (p.252)