Chapter 4 - Research Design Fundamentals Flashcards
Variables
A condition in an experiment or a characteristic of an entity, person, or object that can take on different categories, levels, or values and that can be quantified.
Operational definition
A description of something in terms of the operations (procedure, actions, or processes) by which it could be observed and measured
Independent variables
The variable in an experiment that we specifically manipulated or its observed to occur before the dependent variable, in order to assess its effect or influence
Independent variables may or may not be causally related to the dependent variable
Dependent variables
The outcome that is observed to occur or change after the occurrence or variation of the independent variable in an experiment, or the effect that one wants to predict or explain in correlational research
Outcome variable
Dependent variables may or may not be related causally to the independent variable
Types of dependent variables (3)
- Self-report
- Participants’ explicit attitudes, judgments, thoughts, or characteristics - Behavioural
- Observing and coding participants’ behaviours - Physiological
- Biological data (e.g. heart rate)
Control variables
The factors that are kept the same to ensure that the results are caused by the manipulated variable
A variable that is considered to have an effect on the response measure in a study but that itself is not of particular interest to the researcher
Confounding variables
An independent variable that is conceptually distinct but empirically inseparable from one or more other independent variables.
Confounding makes it impossible to differentiate that variable’s effects in isolation from its effects in conjunction with other variables.
Summary of variables
Situational Variables
* Independent Variables
Response Variables
* Dependent Variables
Participant Variables
* Control Variables
Confounding Variables
Non-Experimental Method
A research project that is lacking manipulation of independent variables by a researcher or random assignment of participants to treat conditions
A form of a correlational study → measure two things and find relation
Correlational Research
A type of study in which relationships between variables are simply
observed without any control over the setting in which those relationships occur or any manipulation by the researcher.
Correlation
The degree of a relationship (usually linear) between two variables, which may be quantified as a correlation coefficient.
Correlation Coefficient (r)
A numerical index reflecting the degree of linear relationship between two variables.
It is scaled so that the value of +1 indicates a perfect positive relationship (such that high scores on variable x are associated with high scores on variable y), –1 indicates a perfect negative relationship (such that high scores on variable x are associated with low scores on variable y, or vice versa), and 0 indicates no relationship.
Correlation Matrix
A symmetrical square matrix displaying the degree of association between all possible pairs of variables contained in a set.
Non-Linear Relationships
An association between two variables in which the direction and rate of change fluctuate.
Non-linear relationships describe any relationship between two variables (x and y) that cannot be expressed in the form y = a + bx, where a and b are numerical constants.
The relationship therefore does not appear as a straight line when depicted graphically.
Mediating Variables
Mediator: an intermediary or intervening variable that accounts for an observed relation between two other variables.
Limitations of Correlational Research
Correlational research cannot explain:
* the direction of cause and effect (did B follow A or did A follow B?)
* a third, unmeasured, variable is responsible for the observed association between two other variables (C is affecting both A and B)
Criteria for Causal Claims
- Coverariation
- Temporal Precedence
- Nonspuriousness
Covariation
Covariation: a relationship between two quantitive variables such that as one variable tends to increase (or decrease) in value, the corresponding values of the other variable tend to also increase (or decrease)
As one variable changes, so does the other one
Method: measurement
Temporal Precedence
Temporal Precedence: in establishing cause effect relationships between two variables, the principle that the cause must be shown to have occurred before the effect
Need cause to occur before effect
Method: experimental conditions & manipulation
Nonspuriousness
Nonspuriousness: there are no plausible alternative explanations for the observed relationship
No other possible explanation for some relationship
Method: random assignment
Experimental Method
Research utilizing randomized assignment of participants to conditions and systematic manipulation of variables with the objective of drawing causal inference
Random Assignment
Random Assignment: the assignment of participants of units to the different conditions of an experiment entirely at random, so that each unit or participant has an equal likelihood of being assigned to any particular condition
Allow us to eliminate undermining differences in a population sample, as conditions should be balanced
Experimental Manipulation
In an experiment, the manipulation of one or more independent variables in order to investigate their effect on a dependent variable
Manipulate independent variable to measure effect on dependent variable
Condition
A level of the independent variable
