"Dependent variables are studied under the supposition or demand that they depend, by some law or rule, on the values of other variables."
A variable in an experiment that is manipulated by the researcher to determine its effect on the dependent variable.
Definition: This topic discusses the meaning of independent variable and how it is used in experimental psychology.
Types of independent variables: This topic explains the different types of independent variables, such as categorical, continuous, and manipulated variables used in experimental designs.
Operational definition: This topic discusses the need for operational definitions of independent variables to ensure consistency in the conducted experiments.
Hypothesis formation: This topic deals with creating testable hypotheses involving independent variables to help predict the relationship between variables.
Independent and dependent variables: This topic deals with understanding and distinguishing between independent variables and dependent variables in experimental psychology.
Experimental design: This topic involves various experimental designs, such as within-subject designs, between-subject designs, and mixed designs, and how independent variables are used in each.
Sampling: This topic discusses how to select samples to ensure representativeness and detect the effects of the independent variable.
Control variables: This topic deals with the importance of controlling other variables that could affect the relationship between the independent variable and dependent variable.
Randomization: This topic provides details on randomization methods and its importance in experimental designs.
Confounding variables: This topic discusses confounding variables and how they affect study validity by creating alternative explanations for the observed effects of independent variables.
Manipulated Independent Variable: This type of independent variable is purposefully changed or manipulated by the researcher to get a certain effect.
Measured Independent Variable: This type of variable is already present and can be measured. It is not changed by the researcher like a manipulated variable.
Discrete Independent Variable: Discrete independent variables have a finite number of distinct values. Examples include number of participants, gender, or yes/no variables.
Continuous Independent Variable: This type of independent variable is a continuous variable, meaning that it can take on any value within a certain range. Examples include age, temperature, or weight.
Categorical Independent Variable: Categorical independent variables are variables that fall into distinct categories or groups, such as race, educational level, or political affiliation.
Quantitative Independent Variable: This type of independent variable represents quantity, such as the number of items in a display or the intensity of a light.
Qualitative Independent Variable: Qualitative independent variables represent a quality, such as the type of emotion present.
Time-Based Independent Variable: Time-based independent variables represent time and can include variables such as duration, frequency, or interval.
Latent Independent Variable: This refers to an unobservable independent variable that affects the outcome of an experiment.
Mediating Independent Variable: This type of independent variable lies between the manipulated variable and the dependent variable, affecting the relationship and outcome.
"Independent variables, in turn, are not seen as depending on any other variable in the scope of the experiment in question."
"Some common independent variables are time..."
"Some common independent variables are time, space, density, mass, fluid flow rate..."
"...previous values of some observed value of interest (e.g. human population size) to predict future values (the dependent variable)."
"...whose variation is being studied, by altering inputs..."
"...also known as regressors in a statistical context."
"In an experiment, any variable that can be attributed a value without attributing a value to any other variable is called an independent variable."
"Models and experiments test the effects that the independent variables have on the dependent variables."
"Sometimes, even if their influence is not of direct interest, independent variables may be included for other reasons..."
"...to account for their potential confounding effect."
"Dependent variables depend... on the values of other variables."
"Some common independent variables are... density..."
"Some common independent variables are time, space, density, mass, fluid flow rate..."
"...previous values of some observed value of interest (e.g. human population size) to predict future values..."
"...whose variation is being studied..."
"...by altering inputs..."
"Models and experiments test the effects that the independent variables have on the dependent variables."
"...any variable that can be attributed a value without attributing a value to any other variable is called an independent variable."
"Sometimes, even if their influence is not of direct interest, independent variables may be included for other reasons..."