Glossary Items Starting with "C"

canonical correlation: A correlation between two sets of variables. The first canonical correlation is derived by computing the linear combination of each set of variables that will give the highest possible correlation. Additional canonical correlations can be computed using different linear combinations of the variables in each set. This technique helps scientists to understand complex relationships between constructs that cannot be easily tapped by a single measure.
carry-over effects: These effects result from of a participant's involvement in one condition affecting his or her performance in all subsequent conditions. Carry-over effects occur only in within-subjects designs.
case study: See case-study level of constraint.
case-study level of constraint: Research in which minimal constraints are placed on participants' behavior. Case-study research usually focuses on the behavior of a single participant.
case study research: See case-study level of constraint.
categorical data: Synonymous with nominal data.
categorical variable: Synonymous with discrete variable. A categorical variable can have only a finite number of values.
causal hypothesis: Usual form of the research hypothesis in experimental research. It states that the independent variable has a causal relationship to the dependent variable. To accept this hypothesis, one must have rejected the null hypothesis and all confounding-variable hypotheses.
causal inference: Conclusion that the change in the independent variable resulted in a change in the dependent variable. It may be drawn only if all potential confounding variables are controlled.
causal relationship: A relationship between variables in which one variable causes a predictable change in the other variable.
causally related: Two variables are causally related if a change in one variable results in a predictable change in the other variable and the change occurs as a direct result of the action of the first variable.
ceiling effect: See scale attenuation effects.
central tendency: Average or typical score in a distribution. Three measures of central tendency are the mean, median, and mode.
chi-square: A statistical distribution that forms the basis for inferential statistics used with nominal data.
classification variables: Organismic or participant variables used to classify participants into discrete groups. Classification variables are used for assigning participants to groups in differential research.
coding data: Process by which scores are assigned to behaviors. The coded data are usually in a form that can be more easily analyzed.
coefficient alpha: An index of internal consistency reliability.
coefficient of determination: The square of the Pearson product-moment correlation. It represents the proportion of variability in one variable that can be predicted on the basis of information about the other variable.
cognitive psychology: The sub-discipline of psychology that studies perceptual processing and basic thought processes.
cognitive science: A broad field that encompasses several disciplines, including behavioral neuroscience, neuroanatomy, neurophysiology, computer science, linguistics, all of which are interested in modeling and understanding the basic brain processes.
cohort effect: The concept that people of a given chronological age in a given culture may behave similarly throughout their lives and different from people of other ages because of shared life experiences.
column means: In factorial designs, one factor is usually illustrated as separate columns of data, in which each column represents a different level of the factor. A second factor might be illustrated as rows of data, in which the different rows represent levels of the second factor. Column means are computed by taking the mean of all participants who appear in a given column regardless of their level on the second factor.
communication phase of research: Research phase in which the rationale, hypotheses, methods, results, and interpretations of the study are presented in oral or written form to other researchers.
complete counterbalancing: See counterbalancing.
computer-analysis programs: Sophisticated computer programs for statistical analyses. Some examples are Biomedical Programs (BMDP); Minitab; Statistical Analysis System (SAS).
computer file: A set of information stored digitally and made available to computers for processing. A computer file can include a program, data, or output.
computer modeling: Using a computer to simulate a psychological process as close as possible to the way in which it is actually performed by people.
concept: A basic principle that forms the building blocks for scientific theories.
conceptual replication: Repeating a study using different operational definitions for the variables.
confidence interval: An interval in which we predict the population parameter to fall with a specified level of confidence. For example, a 95% confidence interval will contain the population parameter 95% of the time.
confidentiality: An ethical requirement in most research; sensitive and personal information provided by participants should be protected and made unavailable to anyone other than the researchers.
confounded: Two variables are said to be confounded if they vary simultaneously so that it is impossible to determine which variable was responsible for the observed change in the dependent variable.
confounding variable: Any uncontrolled variable that might affect the outcome of a study. A variable can confound a study only if (1) there is a mean difference between the groups on the variable and (2) there is a correlation between the variable and the dependent measure.
confounding-variable hypothesis: Actually, a set of hypotheses. Each confounding-variable hypothesis states that a particular confounding variable is responsible for the observed changes in the dependent measure. Each of the hypotheses must be rejected before one can safely conclude a causal relationship between the independent and dependent variables.
constraints: Restrictions places on the researcher in an effort to increase the precision of the research and enhance the validity of the conclusions.
constants: Variables that are prevented from varying (i.e., are held constant).
construct: An idea constructed by the researcher to explain observed events. Constructs are not necessarily direct representations of reality; that is, they are not facts. They are explanatory fictions because, in most cases, we do not know the real reason for a particular event. Once formulated, constructs are used as if they are true (i.e., analogically) to predict relationships between variables in new situations.
construct validity: Validity of a theory. Most theories in science present a broad conceptual explanation of relationships among variables and make many predictions. Construct validity is established by verifying the accuracy of each possible prediction that might be made from the theory. Because the number of predictions is usually infinite, construct validity never can be fully established. However, the more independent predictions from the theory verified as accurate, the stronger will be the construct validity of the theory.
content analysis: Classifying behaviors found in naturalistic or archival records to create data for analysis.
content items: In questionnaires and interviews, content items focus on respondents' opinions, attitudes, and knowledge rather than factual items that can be independently verified.
contingency: A relationship between two or more variables in which the first event is highly predictive of the occurrence of the second event. The relationship between the variables is a probabilistic one and does not necessarily imply a causal connection.
continuous variable: Any variable that can theoretically take on an infinite number of values. Continuous variables are often contrasted with discrete or categorical variables.
contrast: See planned comparison.
control: See control in research.
control group: A group of participants used in either differential or experimental research that serves as a basis of comparisons for other groups. The ideal control group is similar to the experimental group on all variables except the independent variable that defines the group.
control in research: Any procedure that is designed to reduce confounding.
control of variance: Control of error variance and extraneous variance in research.
controlled research: Research that employs adequate controls to rule out competing hypotheses and this draw causal conclusions.
convergent operations: A term for the agreement or similarity among findings from different studies that were carried out with different operational definitions of the same concepts.
convergent validity: Occurs when different studies, using different operational definitions, produce similar findings.
correlated-groups design: Research design in which the participants in each of the groups are related to the participants in the other groups. Two correlated-groups designs are (1) the within-subjects design and (2) the matched-subjects design. These designs provide more powerful tests of the hypotheses because they control for individual differences. They are contrasted with independent-groups design.
correlated-subjects design: See correlated-groups design.
correlated t-test (or direct-difference t-test or matched-pairs t-test): Statistical procedure used to test for mean differences between two groups in a within-subjects or matched-subjects design.
correlation: Degree of relationship between two or more variables.
correlation coefficient: An index of the degree of relationship between variables.
correlational level of constraint: Research designed to quantify the relationship between two or more variables. There is no manipulation of variables and no attempt to draw causal inferences.
correlational research: Research that seeks to measure the relationship between variables without trying to determine causality. The term is sometimes used broadly to include any nonexperimental research design, such as differential research and quasi-experimental designs.
counterbalancing: Control procedure used in within-subjects designs to control for sequence effects. It is most practical when there is a small number of conditions in the study. With complete counterbalancing all possible arrangements of conditions are included; with incomplete counterbalancing only some of the possible arrangements are included.
criterion: The variable that we want to predict in regression.
criterion measure: The variable that we want to predict in regression.
critical thinking: Applying the principles of inference discussed in this textbook to everyday situations.
crossover effect: In quasi-experimental research, a finding in which two nonequivalent groups show one pattern of scores before the manipulation and the reverse pattern of scores after the manipulation. The name derives from the crossing of the lines when such a result is graphed.
cross-cultural research: Exploring psychological phenomena across more than one culture.
cross-sectional design: A design that compares the performance, attitudes, or histories of people of different ages or at different times in history. The groups are defined by the age range of the people in the groups or the historical time in which participants were tested. In a cross-sectional study, participants appear in only one group. This design is often contrasted with longitudinal designs.
cross-sectional research: Research in which a cross-sectional research design is used.
cross-tabulation: Procedure for organizing frequency data that displays the relationship between two or more nominal variables. A cross-tabulation table contains individual cells, with the number in each cell representing the frequency of participants who show that particular combination of characteristics.
cursor: The symbol on the screen of a personal computer that indicates where action will take place. The cursor is moved around the screen a mouse or other pointing device.