More than one factor analysis is called a factorial design
ANOVA with two independent variables is called a two-factor design.
Such a design can be presented in a table with the levels of one factor defining the rows and the levels of the other factor defining the columns.
Each cell in the matrix corresponds to a specific combination of the two factors.
An independent variable is manipulated to create two or more treatment conditions, with the same group of participants compared in all of the experiments.
Study with same group of individuals by observing at two or more different times.
It is is a hypothesis-testing procedure that is used to evaluate mean differences between two or more treatments (or populations).
ANOVA uses sample data as the basis for drawing general conclusions about populations.
t tests are limited to situations in which there are only two treatments to compare.
ANOVA can be used to compare two or more treatments.
