Statistics: a set of mathematical procedures for organizing, summarizing, and interpreting
Population: the set of all individuals of interest in a particular study.
Sample: a set of individuals selected from a population, usually intended to represent the
population in a research study.
Variable: a characteristic or condition that changes or has different values for different
Data (plural): measurements or observations.
Datum (singular): a single measurement or observation; commonly called a score or raw score.
Data set: a collection of measurements or observations.
Parameter: a value, usually a numerical value, which describes a population.Aparameter is
usually derived from measurements of the individuals in the population.
Statistic: a value, usually a numerical value, which describes a sample.Astatistic is usually
derived from measurements of the individuals in the sample.
Descriptive statistics: statistical procedures used to summarize, organize, and simplify data.
Inferential statistics: consist of techniques that allow us to study samples and then make
generalizations about the populations from which they were selected.
Sampling error: a discrepancy, or amount of error, that exists between a sample statistic and the
corresponding population parameter.
Correlational method: two different variables are observed to determine whether there is a
relationship between them (does not show cause).
Experimental method: one variable is manipulated while another variable is observed and
measured. To establish a cause-and-effect relationship between the two variables, an experiment
attempts to control all other variables to prevent them from influencing the results.
Independent variable: the variable that is manipulated by the researcher. In behavioral research,
the independent variable usually consists of the two (or more) treatment conditions to which
subjects are exposed. The independent variable consists of the antecedent conditions that were
manipulated prior to observing the dependent variable.
Dependent variable: the one that is observed to assess the effect of the treatment. Control condition: individuals in a control condition do not receive the experimental treatment.
Instead, they either receive no treatment or they receive a neutral, placebo treatment. The
purpose of a control condition is to provide a baseline for comparison with the experimental
Experimental condition: individuals in the experimental condition do receive the experimental
Quasi-independent variable: in a non-experimental study, the “independent variable: that is
used to create the different groups of scores.
Constructs: internal attributes or characteristics that cannot be directly observed but are useful
for describing and explaining behavior (examples: intelligence, hunger and anxiety).
Operational definition: identifies a measurement procedure (a set of operations) for measuring