"In science and research, an attribute is a quality of an object (person, thing, etc.). Attributes are closely related to variables. A variable is a logical set of attributes."
This topic involves identifying and operationalizing variables used in research studies.
Definition of Variable: Understanding the concept of variables in research and their importance in psychology.
Types of Variables: Categorical and continuous variables, independent and dependent variables, extraneous variables, moderator variables, etc.
Operationalization of Variables: Defining variables in specific, measurable terms that allow for reliable and valid data collection.
Sampling Methods: Random, stratified, cluster, systematic, convenience sampling, etc.
Research Design: Descriptive, correlational, experimental, quasi-experimental, etc.
Measurement Scales: Nominal, ordinal, interval, and ratio measurement scales and their usefulness.
Reliability: Extent to which a research instrument produces consistent, stable results.
Validity: The degree to which a research instrument measures what it claims to measure.
Research Methods: Observational, self-report, experimental, and quasi-experimental methods.
Statistical Analysis: Descriptive and inferential statistical analysis useful for analyzing research data.
Sample Size Determination: Determining the appropriate sample size for research studies.
Hypothesis Testing: Formulating hypotheses and testing them in research.
Statistical Significance: Determining whether study findings are meaningful and significant.
Confidence Intervals: Calculating the intervals within which study results are likely to fall.
Effect Sizes: Determining the practical significance of study findings.
Statistical Power: Determining the likelihood of finding significant results given the size of the sample and research design.
Independent Variable: The independent variable is manipulated by the researcher and is used to measure the effect on the dependent variable. It is the variable that is being tested in the study.
Dependent Variable: The dependent variable is the variable that is being measured in the study. It is affected by the independent variable and is used to evaluate the hypothesis.
Confounding Variable: A confounding variable is a variable that is not being tested in the study but may affect the results of the study. It may lead to inaccurate conclusions if not controlled for.
Control Variable: A control variable is a variable that can be held constant in an experiment in order to ensure that only the independent variable is affecting the dependent variable.
Extranous Variable: An extraneous variable is a variable that can influence the dependent variable but is not of interest to the study.
Covariate: A covariate is a variable that may be related to the dependent variable but is not directly manipulated in the study. It is used to reduce the variability of the dependent variable so that the effects of the independent variable are easier to see.
Mediating Variable: A mediating variable is a variable that is affected by the independent variable and, in turn, affects the dependent variable. It is an intermediate variable that helps explain the relationship between the independent and dependent variables.
Moderating Variable: A moderating variable is a variable that affects the relationship between the independent and dependent variables. It can strengthen or weaken the relationship between the two variables.
Discrete Variable: A discrete variable is a variable that only takes on specific values or categories. Examples include gender, number of siblings, and country of origin.
Continuous Variable: A continuous variable is a variable that can take on any value within a range or interval. Examples include height, weight, and age.
"While an attribute is often intuitive, the variable is the operationalized way in which the attribute is represented for further data processing."
"A domain is a set of all possible values that a variable is allowed to have."
"Values of each variable statistically 'vary' (or are distributed) across the variable's domain."
"The smallest possible domains have those variables that can only have two values, also called binary (or dichotomous) variables."
"Bigger domains have non-dichotomous variables and the ones with a higher level of measurement."
"Bigger domains have non-dichotomous variables and the ones with a higher level of measurement."
"Semantically, greater precision can be obtained when considering an object's characteristics by distinguishing 'attributes' (characteristics that are attributed to an object) from 'traits' (characteristics that are inherent to the object)."
"While an attribute is often intuitive, the variable is the operationalized way in which the attribute is represented for further data processing."
"How high, or how low, is determined by the value of the attribute."
"In science and research, an attribute is a quality of an object (person, thing, etc.)."
"In data processing data are often represented by a combination of items (objects organized in rows), and multiple variables (organized in columns)."
"Values of each variable statistically 'vary' (or are distributed) across the variable's domain."
"The smallest possible domains have those variables that can only have two values, also called binary (or dichotomous) variables."
"Semantically, greater precision can be obtained when considering an object's characteristics by distinguishing 'attributes' (characteristics that are attributed to an object) from 'traits' (characteristics that are inherent to the object)."
"Bigger domains have non-dichotomous variables and the ones with a higher level of measurement."
"While an attribute is often intuitive, the variable is the operationalized way in which the attribute is represented for further data processing."
"In data processing data are often represented by a combination of items (objects organized in rows), and multiple variables (organized in columns)."
"A domain is a set of all possible values that a variable is allowed to have."
"Values of each variable statistically 'vary' (or are distributed) across the variable's domain."