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Introduction to Analysis of Variance - Coggle Diagram
Introduction to Analysis of Variance
Quasi-independent variable
: non manipulated variable to designate groups.
Factor:
In the context of ANOVA, an independent variable or a quasi-independent variable.
Levels:
The individual groups or treatment conditions that are used to make up a factor.
ANOVA:
can be used with either an independent measure or repeated measures. ANOVA can be used to evaluate the results from a research study that involves more than one factor.
Two-factor design or factorial design
: combines two factors with different factors and to mix different designs within one study provides researchers with the flexibility to develop studies that address scientific questions that could not be answered by a single design using a single factor.
Single -factor design:
Studie that use a separate group of participants for each treatment condition.
Statistical Hypothesis for ANOVA: The purpose of the study is to determine whether there are significant differences between the treatment conditions.
Type I Errors and Multiple-Hypothesis Test
s- duplicates what a t-test can produce.
Testwise Alpha level:
the alpha level you select for each individual hypothesis test. The testwise alpha level is the risk of a Type I error, or alpha level, for an individual hypothesis test.
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