What is ANOVA?

History and Definition

ANOVA or Analysis of Variance is a group of statistical models to test if there exists a significant difference between means. It tests whether the means of various groups are equal or not. In ANOVA, the variance observed in a particular variable is partitioned into different components based on the sources of variation. An important fact to note is that while we use ANOVA to find out whether the means differ significantly, we actually compare the variances (hence the name – ANalysis Of VAriance).

While various related methods like hypothesis testing, partitioning of sum of squares, additive models and experimental techniques have been around since the beginning of the 19th century, ANOVA as we know today was first used by Sir Ronald Fisher in 1925 in his book 'Statistical Methods for Research Workers'. Randomization models were first published in 1923 by Neyman. ANOVA is easy to compute and can be manually computed using simple algebra rather than complex matrix calculations. This was one of the reasons for its early popularity.

Benefits and Practical Usage of ANOVA

ANOVA or Analysis of Variance is a group of statistical models to test if there exists a significant difference between means. It tests whether the means of various groups are equal or not. In ANOVA, the variance observed in a particular variable is partitioned into different components based on the sources of variation. An important fact to note is that while we use ANOVA to find out whether the means differ significantly, we actually compare the variances (hence the name – ANalysis Of VAriance).

While various related methods like hypothesis testing, partitioning of sum of squares, additive models and experimental techniques have been around since the beginning of the 19th century, ANOVA as we know today was first used by Sir Ronald Fisher in 1925 in his book 'Statistical Methods for Research Workers'. Randomization models were first published in 1923 by Neyman. ANOVA is easy to compute and can be manually computed using simple algebra rather than complex matrix calculations. This was one of the reasons for its early popularity.

Illustration

Say, a retail chain wants a better understanding of its customers' buying behavior to increase footfalls. It can construct a questionnaire to be administered among mall visitors and also conduct focus groups interviews among select few top malls. Data from these will help create a profile of the customers and ANOVA will help determine which mall is considered best for factors like prices, recreational activities, fashion, value for money and so on. This information can then be used to create better and more effective marketing campaigns to increase footfalls.

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  • Even though most of our communication was done via email, it was extremely easy to work with Research Optimus. Superbly quick turnaround time which was quicker than needed. They were there when I needed them!

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