**A-B-C-D-E-F-G-H-I-J-K-L-M-N-O-P-Q-R-S-T-U-V-W-X-Y-Z**

* abstract population: *The population
about which one ultimately wishes to draw conclusions.

* basic research: *Research emphasizing the solution of theoretical
problems.

* census: *A complete count of the members of a population; also
refers to the count and survey process conducted by the U.S. Census Bureau.

* code: *A translation from raw data
to numbers that can be employed by data entry personnel.

* correlation: *A measure of the
degree of fit (a coefficient indicating the relationship) between two sets of
scores (variables).

* data: *Information about the nature of phenomena derived from
experience or observation.

** demographics**: a variety of
socio-demographic characteristics that can be identified and used to categorize groups with shared
behaviors or traits including: age; gender; ethnicity; income; and education.

* elaboration model: *An image of bivariate and multivariate
cross-tabulation procedures for making sequential inferences from one-shot data.

(1) constructing ethnotheories,

(2) experiencing phenomena, and

(3) constructing common-sense accounts and prophesies.

* evaluation research: *Applied

* experimental pretest: *Observation
prior to introduction of the experimental treatment.

**face*** validity: *The

** goodness of fit**: Degree to which
observed data coincide with theoretical expectations.

* grand mean*: the means of all the
scores in an experiment.

** grouped frequency distribution**: An
arrangement of scores from highest to lowest in which scores are grouped
together into equal-sized ranges called class intervals.

* historical method: *The process of critically examining the records
of the past.

* hypothesis: *A

* independent variable: *A variable
presumed to influence or precede another variable (dependent variable). The
variable is systematically manipulated by the researcher to determine changes in
the dependent variable. Also known as the experimental variable or moderating
variable.

* j-curve*: A severely skewed
distribution with the mode at one extreme.

* laboratory experiment: *An experiment within a deliberately
constructed setting.

* measurement: *The process of creating a correspondence between a
concept and data in specifying that concept.

* method of equal-appearing intervals: *A
technique for constructing an interval scale based on judges' ratings of a large
number of items on the items' degree of "favorableness" to a given
variable.

* nominal scale: *A

* objectivity: *An unprejudiced or open orientation to information
about the nature of phenomena being studied.

* observation: *The act of noting and
recording a phenomenon, often with instruments (cameras, recorders) or note
taking.

* parametric statistics: *Researchers use these statistics when
samples are larger than 30 subjects and are randomly drawn, groups have equal
variances, and data are interval. Examples of these statistics are the T-test
and analysis of variance.

* predictive validity: *The condition
in which scores predict a criterion measure.

* quota sample: *A nonprobability sample that takes into account the
proportion of individuals in different population categories (age, gender, etc.)
within the population. This is a nonprobability type of sample method.

* randomization: *The use of probability sampling to assign subjects
to experimental and control groups.

within methods; and | |

between methods. |

The within-methods approach utilizes only
quantitative (surveys and experiments) or only qualitative (observation and
interviews) approaches. The between-methods approach mixes both quantitative and
qualitative methods.

* regression: *A prediction of the scores (or values) of a given
dependent variable, based on the scores of one or more independent variables.

* reliability: *The degree to which an
operational definition is stable and consistent under similar circumstances.
Reliability amounts to consistency in measurement, the repeatability or
replicability of findings. Specifically, reliability applies to measures of item
consistency (are item responses consistent across constructs?), test stability
(do responses vary when test is given a second time?); and consistency in
administration and scoring (were errors caused by carelessness in administration
or scoring?).

* sample: *A subset of elements selected from a larger set (the
population). The sample is used to make generalizations about the population
from which it was drawn.

(1) proposing theory,

(2) using data to verify theory, and

(3) creating more explanations and accurate predictions of the phenomenon.

* secondary analysis: *The analysis of
available data within a framework that differs from that used in the original
study.

* theory: *Explicit ideas about the nature of phenomena. Theory is an
inter-related set of constructs (or variables) formed into propositions (or
hypotheses) that specify the relationship among the variables.

** treatment**: different levels of the
independent variable.

* type I error: *The rejection of a
correct null hypothesis.

* univariate analysis: *The analysis of single variables as distinct
from relationships among variables.

* validity of measurement: *An indication that the measure accurately
reflects what it is supposed to measure (see also internal and external
validity).

** variance**: the square of the
standard deviation.

* z-score*: A score expressed in
standard-deviation units: used to compare the relative standing of scores in two
different distributions.

**[Class]**

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