varianciaanalízis

Varianciaanalízis, commonly known as ANOVA, is a statistical method used to analyze the differences between the means of two or more groups. It determines if there are any statistically significant differences between the group means, or if the observed differences are likely due to random chance. The technique was developed by statistician Ronald Fisher.

ANOVA works by partitioning the total variation in the data into different sources of variation. The primary goal is to compare the variation between the group means (explained variance) to the variation within each group (unexplained variance). If the variation between groups is significantly larger than the variation within groups, it suggests that the group means are indeed different.

The basic principle of ANOVA involves calculating an F-statistic, which is the ratio of the variance between groups to the variance within groups. A larger F-statistic indicates a greater likelihood that the differences between group means are statistically significant. A p-value is then calculated, and if it falls below a predetermined significance level (commonly 0.05), the null hypothesis that all group means are equal is rejected.

ANOVA is widely used in various fields, including psychology, biology, education, and social sciences, for experimental design and data analysis. There are different types of ANOVA, such as one-way ANOVA, two-way ANOVA, and MANOVA, depending on the number of independent variables and dependent variables involved.