Experimental Design

Research Methods

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Independent variable (treatment)

The independent variable is manipulated by the experimenter.

Examples of independent variables include: Fitness levels, type of practice, contextual interference, strategy for imagery, music …

– Controls– Active and assigned variables– Between subjects and within subjects (repeated

measure) variables

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Within Subjects/Repeated Measure

Order 1 A B C

Order 2 B C A

Order 3 C A B

Counterbalancing, using a Latin Square Design When an experiment has multiple treatments, conditions, or tasks they can be counterbalanced across subjects by using a Latin Square Design. In using a Latin Square Design all orders are not represented; however , all conditions are represented at least once in each position of the order to observe the effects of position and to control for practice, boredom, fatigue….

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Dependent Variable

The dependent variable is the variable measured by the experimenter (e.g., reaction time, heart rate, VO2Max, a survey score)

Concerns

– Standardization– Validity– Reliability– Objectivity– Sensitivity

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Statistical Testing

Categorical Independent Variables; Continuous Dependent Variables

Differences T-test ANOVA

Categorical Independent Variables; Categorical Dependent Variables

Associations Chi squared

Continuous Independent Variables; Continuous Dependent Variables

Relationships Correlation Regression

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Writing Hypotheses

Null

Directional

Alternative

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Null Hypotheses

State the null hypothesis when no literature exists

State the null hypothesis when the literature is controversial or equivocal

State when there is no theoretical direction

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Writing Null Hypotheses

Stated in the null form

– Independent variable (insert name) will not affect dependent variable (insert name).

– Independent variable (insert name) will not associate with the dependent variable (insert name).

– Independent variable (insert name) will not relate to the dependent variable (insert name).

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Directional Hypothesis

State when the literature provides a clear direction

State when the literature is unequivocal

State when good theoretical support exists

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Writing Directional Hypotheses

Independent variable (levels A and B) will affect the dependent variable such that A will be significantly different than B.

Independent variable (levels A and B) will associate with the dependent variable such that B will be significantly associated with B in specific ways.

Independent variable (levels A and B) will relate to the dependent variable such that B will be significantly and positively (or negatively) related to B.

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Writing Problems

How does the independent variable affect the dependent variable?

How does the independent variable associate with the dependent variable?

How does the independent variable relate to the dependent variable?

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Main Effects and Interaction effects

Also you might need to consider interaction and main effects? What if you have two independent variables?

Main effects include the analysis of a single independent variable and all of its levels.

Interaction effects include the analysis of more than one independent variables and the interaction of all of their levels.

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Gender

Male Female Overall Mean

Type of Practice

Massed

Distributed

Control

Overall Mean

Interaction of Two Independent Variables (3*2 factorial design)

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Pure Experimental Designs

Randomized groups Design

Pretest-Posttest Randomized-Groups Design

Solomon Four-Group Design

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Randomized-Groups Design

R T O1

R O2

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Pretest-Posttest Randomized-Groups Design

R O1 T O2

R O3 O4

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Solomon Four-Group Design

R O1 T O2

R O3 O4

R T O5

O6