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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 l.jpg

Experimental Design

The Research Process

Defining a Research Question


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Research & the scientific process

  • What is the scientific process?

    • Rationalism

    • Empiricism

Research is fun


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Scientific theories

  • Inductive theory

    • Specific to general

  • Deductive theory

    • General to specific

  • Functional theory

    • Elements of both

  • Models

    • “mini-theories”


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Inductive approach

Theory

Hypothesis

Pattern

Observations


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Deductive approach

Theory

Hypotheses

Observation

Confirmation/Non-confirmation


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Phases of a research study

  • Idea-generating

  • Problem definition

  • Design of procedures

  • Data collection

  • Data analysis

  • Interpretation


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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


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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


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Limitations of low constraint research

  • Cannot be used to test hypotheses

  • Poor representativeness

  • Poor replicability

  • Observer bias

  • Ex post facto fallacy


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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


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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


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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


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Limitations of experimental designs

  • Not ethical in many situations

  • Often more difficult and costly


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Developing the research question/hypothesis

Initial idea

Initial

observations

Literature search

Problem statement

Operational

definitions

Research hypothesis

(Graziano, 2000)


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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


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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?


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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


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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


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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).


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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.


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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


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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)


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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.


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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.


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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)?