1. Experimental Design The Research Process Defining a Research Question

2. Research & the scientific process What is the scientific process? Rationalism Empiricism

3. Scientific theories Inductive theory Specific to general Deductive theory General to specific Functional theory Elements of both Models “mini-theories”

4. Inductive approach Theory Hypothesis Pattern Observations

5. Deductive approach Theory Hypotheses Observation Confirmation/Non-confirmation

6. Phases of a research study 1. Idea-generating 2. Problem definition 3. Design of procedures 4. Data collection 5. Data analysis 6. Interpretation

7. 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

8. 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

9. Limitations of low constraint research Cannot be used to test hypotheses Poor representativeness Poor replicability Observer bias Ex post facto fallacy

10. 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

11. 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

12. 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

13. Limitations of experimental designs Not ethical in many situations Often more difficult and costly

14. Developing the research question/hypothesis Initial idea Initial observations Literature search Problem statement Research hypothesis Operational definitions (Graziano, 2000)

15. 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

16. 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?

17. 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

18. 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

19. 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).

20. What is a statistical experimental design? 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? Determine the levels of independent variables (factors) and the number of experimental units at each combination of these levels according to the experimental goal. Experimental unit: the unit we apply the factors on to get the response.

21. Example: soft drink beverage Type of sweetener Ratio of syrup to water Carbonation level Temperature 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 Low, High

22. 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) Example: soft drink beverage

23. 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.

24. 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.

25. Example: Which brand of battery should we buy? Three available brands; Prices etc. What is the output variable? What are the input variables (factors)? Battery life.(in hours)

26. Design topics vs. variable types Response (output) Predictor (input) ContinuousCategorical Continuous Response surfaces (RS) Uniform designs (UD) Optimal designs (OD) Standard ANOVA designs (eg. factorial designs) CategoricalUD,OD

27. Prior experimental information The model is known but the parameters are not: Optimal designs The shape of the model is somewhat clear: Response surfaces The model is completely unknown: Uniform designs