Chapter 9

• Experiment


  A research investigation in which conditions are controlled
• Experimental Research


  • Allows a researcher to control the research situation so that causal relationships among variables may be evaluated
  • Independent Variables are expected to determine the outcomes of interest
  • Dependent Variables are the outcomes of interest to the researcher and the decision-makers
• Experimental Research is best for gathering causal information—cause-and-effect relationships
• Subjects


  The sampling units for an experiment, usually human respondents who provide measures based on the experimental manipulation
• Experimental Condition


  One of the possible levels of an experimental (independent) variable manipulation
• Blocking Variables


  Categorical variables included in the statistical analysis of experimental data as a way of statistically controlling or accounting for variance due to that variable
• Covariate


  A continuous variable included in the statistical analysis as a way of statistically controlling for variance due to that variance
• Main Effect


  The experimental difference in dependent variable means between the different levels of any single experimental variable
• Interaction Effect


  Differences in dependent variable means due to a specific combination of independent variables
• Experimental Designs


  • Manipulation of the independent variable
  • Selection and measurement of the dependent variable
  • Selection and assignment of experimental subjects
  • Control over extraneous variables
• Experimental Treatment


  The term referring to the way an experimental variable is manipulated
• Experimental Group


  A group of subjects to whom an experimental treatment is administered
• Control Group


  A group of subjects to whom no experimental treatment is administered
• • One experimental and one control group may not tell the researcher everything he or she wishes to know
  • By analyzing more groups, each with a different treatment level, the researcher can achieve a more precise result
• More Than One Independent Variable


  • Several experimental treatment levels (different values of the independent) may be used
  • More than one independent variable may be examined
  • Cell refers to a treatment combination within an experiment
• The formula for computing the number of cells in an experiment is K = (T1)(T2)..(Tm), where K = the number of cells, T1 = the number of treatment levels for experimental group number one, T2 = the number of treatment levels for experimental group number two, and so forth
• Independent variable


  The variable that is manipulated or changed by the researcher in an experiment
• Manipulation of the independent variable

  1. Several experimental treatment levels (different values of the independent) may be used

  2. More than one independent variable may be examined
• Cell


  A treatment combination within an experiment
• Formula for computing the number of cells in an experiment


  1. K = (T1)(T2)..(Tm)

  2. Where K = the number of cells

  3. T1 = the number of treatment levels for experimental group number one

  4. T2 = the number of treatment levels for experimental group number two

  5. and so forth, through the mth experimental group (Tm)
• This design involves both main effects and interactions
• Dependent variable


  The criterion by which the results of an experiment are judged; a variable expected to be dependent on the experimenter's manipulation of the independent variable
• Selecting dependent variables that are relevant and truly represent an outcome of interest is crucial
• Choosing the right dependent variable is part of the problem definition process
• Thorough problem definition will help the researcher select the most important dependent variable(s) whose results will help managers in decision-making
• Test units


  The subjects or entities whose responses to the experimental treatment are measured or observed
• Systematic or non-sampling error occurs if the sampling units in an experimental cell are somehow different than the units in another cell, and this difference affects the dependent variable
• Randomization


  The random assignment of subject and treatments to groups; it is one device for equally distributing the effects of extraneous variables to all conditions
• Matching


  Involves assigning subjects in a way that a particular characteristic is the same in each group
• Repeated measures


  Experiments in which an individual subject is exposed to more than one level of an experimental treatment
• Experimental confound means that there is an alternative explanation beyond the experimental variables for any observed differences in the dependent variable
• Identifying extraneous variables is important to avoid experimental confounds
• Demand characteristic


  Experimental design element or procedure that unintentionally provides subjects with hints about the research hypothesis
• Demand effect


  Occurs when demand characteristics actually affect the dependent variable
• If participants recognize the experimenter's expectation or demand, they are likely to act in a manner consistent with those expectations, leading to experimenter bias
• Experimenter Bias


  • Occurs when an experimenter's presence, actions, or comments influence the subjects' behavior or sway the subjects to slant their answers in cooperation
• Reducing Demand Characteristics


  1. Use an experimental disguise

  2. Isolate experimental subjects

  3. Use a "blind" experimental administrator

  4. Administer only one treatment level to each subject
• Placebo


  A false experimental treatment disguising the fact that no real treatment is administered
• Placebo Effect


  The effect in a dependent variable associated with the psychological impact that goes along with knowledge of some treatment being administered
• Constancy of Conditions


  Means that subjects in all experimental groups are exposed to identical conditions except for the differing experimental treatments