Chapter 10 review

• Causal claims


  Special because they can lead to advice, treatments, and interventions
• The only way to support a causal claim is to conduct a well-designed experiment
• Simple experiments


  • An experiment showed that taking notes on a laptop rather than in longhand caused students to do worse on a conceptual test of lecture material
  • An experiment showed that babies who watch adults being persistent try harder on a subsequent task
• Experimental variables


  • Independent (manipulated) variable
  • Dependent (measured) variable
• Experiments deliberately keep all extraneous variables constant as control variables
• Why experiments support causal claims


  • They potentially allow researchers to establish covariance, temporal precedence, and internal validity
• Internal validity threats researchers work to avoid


  • Design confounds
  • Selection effects
  • Order effects
• Independent-groups design


  Different participants are exposed to each level of the independent variable
• Posttest-only design


  Participants are randomly assigned to one of at least two levels of an independent variable and then measured once on the dependent variable
• Pretest/posttest design


  Participants are randomly assigned to one of at least two levels of an independent variable and are then measured on a dependent variable twice—once before and once after they experience the independent variable
• How independent-groups designs can establish internal validity


  • Random assignment or matched groups can help minimize selection effects
• Within-groups design


  The same participants are exposed to all levels of the independent variable
• Repeated-measures design


  Participants are tested on the dependent variable after each exposure to an independent variable condition
• Concurrent-measures design


  Participants are exposed to at least two levels of an independent variable at the same time and then indicate a preference for one level (the dependent variable)
• Benefits of within-groups designs


  • Treat each participant as his or her own control
  • Require fewer participants than independent-groups designs
• Potential issues with within-groups designs


  • Order effects
  • Demand characteristics
• Construct validity


  Evaluating whether the variables were manipulated and measured in ways consistent with the theory behind the experiment
• External validity


  Evaluating whether the experiment's results can be generalized to other people or to other situations and settings
• Statistical validity


  Evaluating the effect size, precision of the estimate as assessed by the 95% CI, and whether the study has been replicated
• Internal validity


  Evaluating for design confounds and whether the researchers used techniques such as random assignment to minimize threats
• Experiment


  A study in which at least one variable is manipulated and another is measured
• Manipulated variable


  A variable in an experiment that a researcher controls, such as by assigning participants to its different levels (values)
• Measured variable


  A variable in a study whose levels (values) are observed and recorded
• Independent variable


  In an experiment, a variable that is manipulated. In a multiple-regression analysis, a predictor variable used to explain variance in the criterion variable
• Condition


  One of the levels of the independent variable in an experiment
• Dependent variable


  In an experiment, the variable that is measured. In a multiple-regression analysis, the single outcome, or criterion variable the researchers are most interested in understanding or predicting
• Control variable


  In an experiment, a variable that a researcher holds constant on purpose
• Comparison group


  A group in an experiment whose levels on the independent variable differ from those of the treatment group in some intended and meaningful way
• Control group


  A level of an independent variable that is intended to represent "no treatment" or a neutral condition
• Treatment group


  The participants in an experiment who are exposed to the level of the independent variable that involves a medication, therapy, or intervention
• Placebo group


  A control group in an experiment that is exposed to an inert treatment, such as a sugar pill
• Confound


  A general term for a potential alternative explanation for a research finding; a threat to internal validity
• Design confound


  A threat to internal validity in an experiment in which a second variable happens to vary systematically along with the independent variable and therefore is an alternative explanation for the results
• Systematic variability


  In an experiment, a description of when the levels of a variable coincide in some predictable way with experimental group membership, creating a potential confound
• Unsystematic variability


  In an experiment, a description of when the levels of a variable fluctuate independently of experimental group membership, contributing to variability within groups
• Selection effect


  A threat to internal validity that occurs in an independent-groups design when the kinds of participants at one level of the independent variable are systematically different from those at the other level
• Random assignment


  The use of a random method (e.g., flipping a coin) to assign participants into different experimental groups
• Matched groups


  An experimental design technique in which participants who are similar on some measured variable are grouped into sets; the members of each matched set are then randomly assigned to different experimental conditions
• Independent-groups design


  An experimental design in which different groups of participants are exposed to different levels of the independent variable, such that each participant experiences only one level of the independent variable
• Within-groups design


  An experimental design in which each participant is presented with all levels of the independent variable