**
Graziano & Raulin**

**Research Methods (8th edition)**

- naive empiricism
- Extreme dependence on one's personal experience in order to
accept events as facts. For example, "If I can't see it, then it
does not exist."

- naturalistic level of constraint
- Research carried out in natural settings in which the
researcher makes no attempt to manipulate the environment as
part of the research.

- naturalistic observation
- Observing the natural flow of behavior in natural settings.

- negative correlation
- Relationship between two variables in which an increase in
one variable predicts a decrease in the other.

- negative practice effects
- A decrease in performance on a dependent measure that
results from previous exposure of the participant to the
measurement procedures.

- negatively skewed
- When scores are concentrated near the top of the
distribution.

- neuro-networks
*Connectionist models*are sometimes referred to as neuro-networks because they are designed to resemble the massive interconnections between units that are typical of brain neurons. However, most theorists argue that the connectionist models now in use are dramatic oversimplifications of neural processes and, therefore, one should be cautious in using terms such as neuro-networks to describe them.

- neuropsychology
- A field that studies the relationships of brain functioning
to behavior.

- neurotransmitter agonists
- A chemical substance that enhances the action of a
neurotransmitter.

- neurotransmitter antagonists
- A chemical substance that blocks the action of a
neurotransmitter.

**no-treatment control group**- A control group in a treatment study that receives no
treatment of any kind.

- nominal data
- Data produced when a nominal scale of measurement is used.
Nominal data are frequencies of participants in each of the
specific categories.

- nominal fallacy
- The tendency to confuse a label for a behavior as the
explanation for the behavior. For example, labeling people as
kind because they do many kind things for other people is
reasonable, but it is unreasonable to then say that they do
those kind things because they are kind people.

- nominal scale
- Scale of measurement in which only categories are produced
as scores. Examples are diagnostic classification, gender of the
participant, and political affiliation.

- nonequivalent control-group design
- Quasi-experimental design in which two or more groups that
may not be equivalent at the beginning of the study are compared
on the dependent measure.

- nonexperimental designs
- Any research design that fails to provide adequate controls
for confounding.

- nonexperimental approaches
- See
*nonexperimental designs*.

- nonlinear relationship
- Any relationship between two or more variables that is
characterized by a
*scatter plot*in which the points tend to cluster around a curved instead of a straight line. Most correlations coefficients are insensitive to nonlinear relationships.

- nonmanipulated factors
- Independent variables in a factorial design in participants
are assigned to groups on the basis of some preexisting factor.
See
*differential research*.

- nonmanipulated independent variable
- The preexisting variable that determines group membership in
a
*differential research*study.

- nonparametric statistics
- Inferential statistical procedures that do not rely on
estimating such population parameters as the mean and variance.

- nonprobability sampling
- Any sampling procedure in which some participants have a
higher probability of being selected than other participants or
the selection of a given participant changes the probability of
selecting other participants. Often contrasted with
*probability sampling*.

- nonreactive measure
- Any dependent measure that provides consistent scores
regardless of whether the participant is aware or unaware of
being measured.

- nonsystematic within-groups variance
- Variance due to random factors that affect some participants
more than others. Also called
*error variance*.

- N-of-one designs
- See
*single-subject experimental designs*.

- normal distribution
- Distribution of scores that is characterized by a
bell-shaped curve in which the probability of a score drops off
rapidly from the midpoint to the tails of the distribution. A
true normal curve is defined by a mathematical equation and is a
function of two variables (the mean and variance of the
distribution). Normal distributions are useful in psychology
because psychological variables tend to show distributions that
are close to normal.

- null hypothesis
- States that the participants from each group are drawn from
populations with identical population parameters. The null
hypothesis is tested by
*inferential statistics*.