correlation is used when there is metric data and chi square is used when there is categorized data.
sayan chakrabortty
Chat with our AI personalities
The coefficient of determination R2 is the square of the correlation coefficient. It is used generally to determine the goodness of fit of a model. See: http://en.wikipedia.org/wiki/Coefficient_of_determination for more details.
none
Given co-efficient of determination, r2 = 0.81. co-efficient of correlation, r = square root of 0.81 = +0.9, if the data have move in the same direction.(Let x and y as variables then x and y have linear relationship and x increase or decrease and y also have increase or decrease) = -0.9, if the data have move in the opposite direction.(Let x and y as variables then x and y have linear relationship and x decrease or increase and y is also increase or decrease)
The coefficient, also commonly known as R-square, is used as a guideline to measure the accuracy of the model.
The larger the difference, the larger the value of chi-square and the greater the likelihood of rejecting the null hypothesis