CHAPTER 7,8,9 Flashcards
is the variable (antecedent condition) an experimenter intentionally manipulates.
independent variable
are the values of the IV created by the experimenter.
levels
is the outcome measure the experimenter uses to assess the change in behavior produced by the independent variable.
dependent variable
specifies the exact meaning of a variable in an experiment by defining it in terms of observable operations, procedures, and measurements.
operational definition
specifies the exact procedure for creating values of the independent variable.
experimental operational definition
specifies the exact procedure for measuring the dependent variable.
measured operational definition
assigns items to two or more distinct categories that can be named using a shared feature, but does not measure their magnitude.
nominal scale
measures the magnitude of the dependent variable using ranks, but does not assign precise values.
ordinal scale
measures the magnitude of the dependent variable using equal intervals between values with no absolute zero point.
interval scale
measures the magnitude of the dependent variable using equal intervals between values and an absolute zero.
ratio scale
refers to the consistency of experimental operational definitions and measured operational definitions.
Reliability
is the degree to which observers agree in their measurement of the behavior.
Interrater reliability
means the degree to which a person’s scores are consistent across two or more administrations of a measurement procedure.
Test-retest reliability
measures the degree to which different parts of an instrument (questionnaire or test) that are designed to measure the same variable achieve consistent results.
Interitem reliability
means the operational definition accurately manipulates the independent variable or measures the dependent variable.
Validity
is the degree to which the validity of a manipulation or measurement technique is self-evident.
Face validity
means how accurately a measurement procedure samples the content of the dependent variable.
Content validity
means how accurately a measurement procedure predicts future performance.
Predictive validity
is how accurately an operational definition represents a construct.
Construct validity
is the degree to which changes in the dependent variable across treatment conditions were due to the independent variable.
Internal validity
occurs when an extraneous variable systematically changes across the experimental conditions.
Confounding
occurs when an event outside the experiment threatens internal validity by changing the dependent variable.
History threat
is produced when physical or psychological changes in the subject threaten internal validity by changing the DV.
Maturation threat
is when changes in the measurement instrument or measuring procedure threatens internal validity.
Instrumentation threat
threat occurs when subjects are assigned to conditions on the basis of extreme scores, the measurement procedure is not completely reliable, and subjects are retested using the same procedure to measure change on the dependent variable.
Statistical regression threat
occurs when individual differences are not balanced across treatment conditions by the assignment procedure.
Selection threat
occurs when subjects drop out of experimental conditions at different rates.
Subject mortality threat
occur when a selection threat combines with at least one other threat (history, maturation, statistical regression, subject mortality, or testing).
Selection interactions
This section provides the reader with sufficient detail (who, what, when, and how) to exactly replicate your study.
Method section
is appropriate when the equipment used in a study was unique or specialized, or when we need to explain the capabilities of more common equipment so that the reader can better evaluate or replicate the experiment.
Apparatus section
are aspects of the testing situation that need to be controlled
Physical variables
completely removes extraneous physical variables from the experimental situation (e.g., soundproofing a room).
Elimination
controls extraneous physical variables by keeping all aspects of the treatment conditions identical, except for the independent variable.
Constancy of conditions
are aspects of the relationships between subjects and experimenters that can influence experimental results.
Social variables
are cues within the experimental situation that demand or elicit specific participant responses.
Demand characteristics
in this experiment, subjects are not told their treatment condition.
single-blind experiment
is when a subject receives an inert treatment and improves because of positive expectancies.
placebo effect
is a false plausible explanation of the experimental procedures to disguise the research hypothesis from the subjects.
cover story
is any behavior by the experimenter that can confound the experiment.
Experimenter bias
is the phenomenon in which experimenters treat subjects differently based on their expectations and their resulting actions influence subject performance.
Rosenthal effect
Other names of Rosenthal Effect
Pygmalion effect and self-fulfilling prophecy
control both demand characteristics and experimenter bias, since both the experimenter and subjects are blinded.
Double-blind experiments
are more sociable, score higher in social desirability, hold more liberal social and political attitudes, are less authoritarian, and score higher on intelligence tests than no volunteers.
Volunteers
are extraneous variables produced by experimental procedures created by the research setting environment, like assignment of participants to conditions.
Context variables
When we allow subjects to sign up for experiments whose titles differ in their appeal that could result in a biased sample threatening _______
external validity
details an experimenter’s plan for testing a hypothesis.
design
A researcher mainly selects an experimental design on the basis of three factors
- The number of independent variables in the hypothesis.
- The number of treatment conditions needed to fairly test the hypothesis
- Whether the same subjects are used in each of the treatment conditions.
in this design, a subject participates in only one condition of the experiment.
between-subjects design
determines whether we can generalize our results to the entire population from which the sample was drawn.
representativeness
increases an experiment’s external validity.
Random sampling
is a statistical estimate of the size or magnitude of a treatment effect.
Effect size
determines the number of subjects required to detect a treatment effect.
Effect size
Using these charts, researchers determine the number of subjects required for an expected effect size
power charts
involves the creation of two separate groups of subjects.
two group design
Two versions of the two group design are
- The two independent groups design and
2. Two matched groups design.
A design where there is one IV with two levels and subjects are randomly assigned to one of the two conditions. This design includes:
- Experimental Group-Control Group design and
2. Two-Experimental Groups design.
involves assigning subjects to conditions so that each subject has an equal chance of participating in each condition.
Random assignment
presents a value of the independent variable.
experimental condition
presents a zero level of the independent variable.
control condition
this group receives a level of the IV
experimental group
this group receives the same procedures, but receives no treatment.
control group
This design is appropriate if there is one independent variable with two levels and if we can assume that randomization will control extraneous variables.
two experimental groups design
is used to create groups that are equivalent on potentially confounding subject variables.
Matching
is a between-subjects design with more than two levels of an independent variable.
multiple groups design
in this group design, we randomly assign subjects to one of the treatment conditions.
multiple independent groups design
is a process for randomly assigning equal numbers of subjects to conditions.
Block randomization
is a trial run of the experiment that uses a few subjects.
pilot study
these can all help determine the number of treatments.
hypothesis, prior research, pilot study results, and practical limits
