 # Variance: Analysis Of Means

1045 Words5 Pages
Analysis of Variance (ANOVA) is a statistical method used to test differences between two or more means. Though it is called "Analysis of Variance" but actually it is "Analysis of Means."
ANOVA was developed by Ronald Fisher in 1918 and is the extension of the t and the z test. Before the use of ANOVA, the t-test and z-test were commonly used. But the problem with the T-test is that it cannot be applied for more than two groups. This test is also called the Fisher analysis of variance, which is used to do the analysis of variance between and within the groups whenever the groups are more than two. If the Type one error is set to be .05, and there are several groups, each time a mean is tested against another there would be a .05 probability
You compare the differences in the samples to see if they are the same or statistically different while still accounting for sampling error.

For example, a teacher might have data on student performance in non-assessed tutorial exercises as well as their final grading. The teacher is interested in knowing if tutorial performance is related to final grade. ANOVA allows breaking up the group according to the grade and then knowing if performance is different across these grades.

Types of ANOVA

These days, researchers are using ANOVA in many ways. The use of ANOVA depends on the research design. Commonly, researchers are using ANOVA in three ways:
• One-way ANOVA
• Two-way ANOVA
• N-way Multivariate ANOVA.

One-Way: When we compare more than two groups, based on one factor (independent variable), this is called one way ANOVA. For example, it is used if a manufacturing company wants to compare the productivity of three or more employees based on working hours. This is called one way