Exam 2 Content 

Chapter 3:

  • Operational Definition: a definition that tells the reader exactly what was done to produce a phenomenon or to measure some variable.
  • Reliability: the same procedures produce the same results
  • Validity: the extent to which a measurement technique measures what it’s supposed to measure
  • Internal Validity: the extent to which the design of an experiment ensures that the IV, not some other variable, caused the measured difference in the DV
  • Confound: a factor that yields alternative explanations for a study’s results. These limit internal validity.
    • Experimenter Effect: a confound where the experimenter affects the results.
    • Demand Characteristics: the cues participants use to determine what is expected of them in a study.
  • External validity: the generalizability of the results of an investigation beyond the specific participants, measures, and site of the research.
  • Extraneous Variables: factors other than the Independent variables that could possibly affect the outcome of the study.
  • Random Selection: all members of a population are equally as likely to be chosen
    • Convenience Sample: participants are not randomly chosen, but instead happen to be in the right place at the right time.
  • Random Assignment: use of a procedure so that each participant from the population is equally as likely to be assigned to either condition.
  • Null Hypothesis (H0): no difference in the groups being compared.
  • Alternative Hypothesis (HA): hypothesis upon which the researcher’s prediction is being made.
  • Type I Error: reject the null hypothesis when it is true
  • Type II Error: fail to reject the null hypothesis when it is false (less serious)

Chapter 6:

  • Experiments: investigations in which the researcher manipulates an IV to determine if there are any differences in the DV among equivalent groups of participants
    • Three requirements to yield causal results:
    • equivalent groups— the best way is random assignment
    • temporal priority
    • no confounds
  • Quasi-Experimental: a study in which groups of participants are NOT equal.
  • Correlational Study: an investigation that explores the effect of a subject variable on a dependent measure.
  • Between-subjects design: the performance of participants in one or more groups is compared with the performance of participants in another group.
  • Selection Bias: When the experimenter or participant chooses which group the participants are in.
  • Matching: identifying pairs (or more) of participants that measure similarly on a characteristic is related to the DV and then randomly assigning each participant to a certain group
  • Pretest: given before the IV is manipulated
  • Within-Subjects Design: one sample of participants is tested two or more times, providing two or more comparable scores at one testing.
    • repeated measures
    • pretest-postest
    • longitudinal
  • Cross-sectional Design: used by researchers to look at differences between different age groups
  • Extraneous variables: variables that can affect the dependent variable
    • hold constant: a variable all groups in the study will have the same level of the extraneous variable
    • counterbalance: extraneous variables will be a part of every condition (more advantageous at yielding external validity than holding constant)
  • Instrumentation Effect: the dependent variable is measured changes in accuracy over time.
  • Subject Mortality: when volunteers for the experiment are provided informed consent before the experiment begins, but quit part of the way through.
    • Nonsystematic Subject Mortality: when a participant leaves a study for a reason unrelated to the subject of the experiment itself
    • Systematic Subject Mortality: the participants who quit are distributed unevenly among the groups.
  • Comparable Treatment of Groups: the researcher treats the experimental groups as evenly as possible, except for the manipulation of the IV.
  • Error Variance: the natural, random fluctuation in scores caused by factors other than the IV.

Chapter 7:

  • Pretest-Postest Design: one group of participants is tested twice using the same measurement tool, once before and after the IV is manipulated in some way.
  • Repeated-Measures Design: multiple measurements per participant, used when a single testing session the participants provide multiple pieces of data.
  • Longitudinal Design: looks for changes that occur over time.
  • carryover effect: when participants perform a task numerous times, and their performance in earlier trials affects their performance in later trials
  • practice effect: when, through repetition, the participant’s performance improves
  • fatigue effect: participants repeat the task and their performance declined
  • history effect: the result of an event that occurs outside the experiment at the same time that the IV is being changed
  • maturation effect: any changes in behavior caused by the passage of time
  • testing effect: when tested repeatedly, the experience on a previous test is likely to affect the results of the next test
  • Regression toward the mean: the phenomenon in which extreme scores closer to the mean
  • Counterbalancing: presenting the experimental conditions to participants in different orders so that carryover effects can be controlled
  • Complete within-subjects design: all the participants experience each experimental condition several times until they have each received all possible orders of the condition
    • ABBA
    • block randomization
  • incomplete within-subjects design: each participant receives a unique order of the conditions at least once, but does not receive all possible sequences of conditions
    • random order with rotation
    • balanced Latin square