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42 Cards in this Set

  • Front
  • Back


Differentiates between a set of groups being compared in an experiment


different values of the independent variable that are selected to create the treatment condition


How is the group treated in an experiment.


Conditions that change or have different values for different individuals

Characteristics of a variable

Needs to be observable. Can be measured directly or indirectly. Needs to be replicable. Can be consistently measured. Must have 2 levels/values.

Operational Definitions

Procedure for indirectly measuring and defining variables that cannot be observed or measured directly. Good operational definitions are clear, precisely articulated.


Accurate measurement


Consistent measurement

Types of variables

Situational, Response, Participant, Mediating

Situational Variables

Describes characteristics of a situation or environment. What aspect of the environment changes for the subjects. Most experimentally manipulated variables are in this category.

Response variables

Responses or behaviours of subjects/ participants. Typically the variable that you are measuring when you manipulate the situational variable.

Participant variables

Differences between individuals. Constant within individuals, variable between individuals. Gender, height, genetic composition

Mediating variables

Help explain how and why a relationship exists between two other variables. Independent variable causes a mediating variable that then causes a dependent variable. Typically found in psychological theories, and prevention and treatment research.

Continuous variable

Measured along a continuum. As a whole or fractional unit. Can have infinite decimal places if desires. weight, temperature, duration of drug abuse.

Discrete Variable

Measured in whole units or categories that are not distributed on a continuum. MCAT score, gender

Quantitative variables

Varies by amount, measured in numeric units. Both discrete and continuous variables can be quantitative.

Qualitative variables

Varies by type or class, often a category or label for a group of events. Non-numeric. Depression, kinds of drug use, health condition.

Independent variable

Plotted on the x axis. Manipulated variable. Determined by the experimental design/ researcher. Known in advance. Determined by treatment conditions.

Dependent variable

plotted on the y axis. This is where we observer the change that was effected by the independent variable. Essentially this variable is dependent on the independent variable.

control variable

All other variables. that should be controlled. Potential independent variables that are held constant during an experiment.

Confounding variable.

Ideally none. Potentially independent variables that are not held constant because they are over looked. Confounding variables result in inability to determine what the experimental outcomes indicate.

Reducing Error

Error is reduced, never eliminated when the testing procedure is standardized. Sources of error are experimenter, environment, participant, and instrument.

Sources of Error: experimenter

Ensure experimenter behaves similarly with each subject. Animal habituation and handling. Same clothing/experimenter/script per participant.

Sources of Error: Environmental

Choose best conditions for testing, temperature, time of day, noise level.

Sources of Error: Participants/ subject

Inclusion/ exclusion criteria decided before starting the study. Animal body weight, overall health.

Sources of Error: Instrument

Using same instruments. Calibration.


Shows correlation, Two events are related. Line of fit, line that closely approximates data. Correlation Coefficient, measures how well data is modelled by a linear equation.

Nominal Scale

Label/category. Qualitative differences in levels of a variable. Used for categorization, Measurements where numbers represent something/ someone. Resulting data indicated the proportion of subjects/ participants in each category. Resulting data indicates the proportion of subjects/ participants in each category: Gender, fur coat colour, genotype.

Ordinal Scale

Rank order. Measurements that convey order or rank. the numbers are meaningful but distance between numbers are not necessarily equal. Limitation is the difference between consecutive places within the rank, can be highly variable: grades A-B not the same as C-D. Rank order of athletes during a race, University ranking.

Interval scale

Rank order at equal intervals. Similar to ordinal scale, but intervals between adjacent values are constant. No true zero, temperature. 0 temperature is not no temperature; arbitrary zero point. Rating scale in behavioural sciences.

Ratio Scale

Rank order at equal intervals with zero. Similar to the interval scale but it has a zero. Here zero means the absence of a phenomenon. Most informative scale of measurement.

Ratio vs. Interval

The way you conceptualize your variable dictates whether or not its a ratio or an interval scale.

Different types of validity of measurement

Face, concurrent, predictive, construct, convergent, divergent.

Face validity

Looks like a good measure. Sometime useful for disguising true purpose of measurement.

Predictive validity

Scores obtained from a measure predict future behaviour. But can only be assessed after the experiment is done.

Construct validity

Scores obtained from a measure behaves exactly as everything that is known about your construct.

Concurrent Validity

Scores obtained using a new measure correlates with previously established measure. Previous measure is usually the gold standard. New measure is done at the same time as the gold standard. Strong positive correlation between new and old measurement.

Convergent validity

two measurements give strongly related scores and converge on the same construct. No emphasis on timing or gold standard. Two different methods of testing show positively related scores.

Divergent Validity

Same method to measure two different constructs to discriminate between the constructs. demonstrate that your measurement does not correlate with the two constructs.

Types of reliability

Test - retest. Inter rater reliability


determine the correlation between the scores from measurements taken at two time points.

Inter-rater reliability

Determine the correlation between scores from two independent scores.