ANOVA is a parametric statistical technique that helps in finding out if there is a significant difference between the mean of three or more groups.
It is a type of hypothesis test, used to check whether there is a statistically significant difference between the mean of three or more groups that has been divided into one factors.(factor will be independent variable)
It is a type of hypothesis test, used to check whether there is a statistically significant difference between the mean of three or more groups that has been divided into two factors. (factors will be independent variable)
- the samples have a normal distribution.
- the samples are selected at random and should be independent of one another.
- all groups have equal standard deviations.
- H0 -> μ1 = μ2 = μ3 (It implies that the means of all the population are equal).
- Ha -> At least one difference among the means.
In case of comparing two groups, t-test is preferred over ANOVA. In the case of comparing three or more groups, ANOVA is preferred.
ANOVA is a method to determine if the mean of groups are different. In inferential statistics, we use samples to infer properties of populations. Statistical tests like ANOVA help us justify if sample results are applicable to populations.
ANOVA result is based on the F ratio
F ratio is a measure of the comparison between the variation between groups and variation withing groups.
Higher F ratio values indicate the variation between groups is larger than the individual variation of groups. In such cases, it is more likely that the mean of the groups are different.