The dependent variable fluctuates depending on the magnitude of the independent variable, according to ANOVA. Consider the following scenario: Social media use is your independent variable, and you allocate groups to low, medium, or high levels of social media use to see if there is a difference in the number of hours of sleep per night.
ANOVA is a sort of hypothesis testing that analyses the variance of the different survey groups to determine the experimental outcomes. It is typically used to determine the dataset's outcome.
ANOVA, like the t-test, can be used to determine whether differences between groups of data are statistically significant. It analyses the levels of variance within the groups by taking samples from each of them.
There are two independent variables in a two-way ANOVA. A two-way ANOVA, for example, lets a business to analyse worker productivity across two independent factors, such as department and gender. It's used to track the interaction between the two variables. It examines the impact of two variables at the same time.