Anova is a statistical technique that
has the ability to assess the potential difference in a scale-level dependent variable
by using a nominal-level variable which has two or more categories. Anova was
first developed in 1918 by Ronald Fisher. Anova extends the t and Z test which
had the problem whereby it only allowed the nominal level variable to possess
two categories. The Anova test is also called the Fisher analysis of Variance.
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Analysis of Covariance
Hypothesis Testing and ANOVA
ANOVA with Random Factors and
Randomized Blocks ANOVA
Assumptions and Effects of
Repeated measures ANOVA
Contrast Analysis and Post
Categories of ANOVA
Students and researchers use ANOVA in varied
ways. The research design is what dictates the use of ANOVA .there are three
common ways in which ANOVA is used, these are: One-way ANOVA, two-way ANOVA,
and N-way ANOVA
Ø One-Way ANOVA
There is just one independent variable in one
Ø Two-Way ANOVA
Two ways ANOVA uses two independent variables.
It has the ability to examine the relationship between two independent variables.
The two-way ANOVA is also referred to as factorial ANOVAs
Ø N-Way ANOVA
This allows for researchers to use more than
two independent variables. The n-way ANOVA has n which
bears the number of all the independent variables.
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