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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