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Experimental Design. The Research Process Defining a Research Question. Research & the scientific process. What is the scientific process? Rationalism Empiricism. Research is fun. Scientific theories. Inductive theory Specific to general Deductive theory General to specific
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Experimental Design The Research Process Defining a Research Question
Research & the scientific process • What is the scientific process? • Rationalism • Empiricism Research is fun
Scientific theories • Inductive theory • Specific to general • Deductive theory • General to specific • Functional theory • Elements of both • Models • “mini-theories”
Inductive approach Theory Hypothesis Pattern Observations
Deductive approach Theory Hypotheses Observation Confirmation/Non-confirmation
Phases of a research study • Idea-generating • Problem definition • Design of procedures • Data collection • Data analysis • Interpretation
Research Designs* • Naturalistic observation • Case study • Correlational • Differential • Experimental Constraint level • Taken from Graziano • Not all research studies fit neatly into one of these categories
Strengths of low constraint research • Can be used to generate hypotheses • Can be used to negate a proposition • Can be used to identify contingent relationships
Limitations of low constraint research • Cannot be used to test hypotheses • Poor representativeness • Poor replicability • Observer bias • Ex post facto fallacy
Strengths of correlational/differential research • Good for situations where manipulation of an independent variable is not practical or ethical! • Higher constraint than observations or case studies
Limitations of correlational/differential research • Influence of confounding variables • Correlation does not imply causation • A causes B, B causes A, some other factor causes A and B • The researcher measures but does not manipulate the variables
Strengths of experimental designs • Causation can be determined (if properly designed) • The researcher has considerable control over the variables of interest • Can be designed to evaluate multiple independent variables
Limitations of experimental designs • Not ethical in many situations • Often more difficult and costly
Developing the research question/hypothesis Initial idea Initial observations Literature search Problem statement Operational definitions Research hypothesis (Graziano, 2000)
Good characteristics of a problem statement • States the expected relationship between variables • The problem should be in the form of a question • Implies the possibility of an empirical test of the problem
Problem statements • Observations & Case studies • Given A what is the probability of B? • Correlational research • Is variable A correlated to a specific change in variable B • Differential research • Will group A differ from group B by variable X? • Experimental design • Does variable A cause a specific change in variable B?
Operational definitions • Definition of the variables of interest • How are they defined? • How will they be measured? • A good operational definition of variables defines the procedure so precisely that another researcher could replicate it
Research hypothesis • Develop the problem statement into a specific testable prediction • States the direction • Represents a declarative statement e.g., Brown bullheads exposed to PAH-contaminated sediments will develop skin tumors at a higher rate than controls
What is an experiment? • An inquiry in which an investigator chooses the levels (values) of input or independent variables and observes the values of the output or dependent variable(s).
What is a statistical experimental design? Determine the levels of independent variables (factors) and the number of experimental units at each combination of these levels according to the experimental goal. • What is the output variable? • Which (input) factors should we study? • What are the levels of these factors? • What combinations of these levels should be studied? • How should we assign the studied combinations to experimental units? Experimental unit: the unit we apply the factors on to get the response.
Example: soft drink beverage • What is the output variable? Taste of the drink; score 1 to 10 (from poor to good) • What factors and at which levels should we study? A, B • Type of sweetener • Ratio of syrup to water • Carbonation level • Temperature Low, High
Example: soft drink beverage • What combinations of factors should be studied? All 2x2x2x2 combinations. • How should we assign the studied combinations to • experimental units? Assign equal number of units to each combination. (unit: the “null” beverage or say the plain water)
The Six Steps of Experimental Design • Plan the experiment. • Design the experiment. • Perform the experiment. • Analyze the data from the experiment. • Confirm the results of the experiment. • Evaluate the conclusions of the experiment.
Plan the Experiment • Identify the dependent or output variable(s). • Translate output variables to measurable quantities. • Determine the factors (input or independent variables) that potentially affect the output variables that are to be studied. • Identify potential combined actions between factors.
Example: Which brand of battery should we buy? Three available brands; Prices etc. • What is the output variable? Battery life. (in hours) • What are the input variables (factors)?
