The analysis of variance frequently referred to us ANOVA.
It is a statistical technique, specially designed to test whether the means of more than 2 quantitative populations are equal.
The analysis of variance technique developed by prof. R.A Fischer in 1920’s is capable of fruitful application to a diversity of practical problems.
Basically it consist of classifying and cross classifying statistical results and testing whether the means of a specified classification differ significantly
Eg. The output of a given process might be cross classified by machines & operators. Each operator having worked on each machine.
One way Classification
In this the data are classified according to only one criteria.The null hypothesis is
Correlation in Bivariate frequency Table
In a bivariate distribution the data are fairly large ,they must be summarized in the form of a two way table. Here for each variable the values are grouped into various classes( not necessarily the same for both the variable) keeping in view the same consideration as in the case of univariate distribution.
Eg. If there are m classes for the x variable series and n classes for the y variable series then there will be m*n cells in the two way table. By going through the different pairs of the values(x,y) and using tally marks we can find the frequency for each cell and thus obtained the so called bivariate frequency table .