In Statistical Analysis, the coefficient of determination method is used to predict and explain the future outcomes of a model. This method is also known as R squared. This method also acts like a guideline which helps in measuring the model’s accuracy. In this article, let us discuss the definition, formula, and properties of the coefficient of determination in detail.
Table of Contents:
Coefficient of Determination Definition
The coefficient of determination or R squared method is the proportion of the variance in the dependent variable that is predicted from the independent variable. It indicates the level of variation in the given data set.
- The coefficient of determination is the square of the correlation(r), thus it ranges from 0 to 1.
- With linear regression, the coefficient of determination is equal to the square of the correlation between the x and y variables.
- If R^{2} is equal to 0, then the dependent variable cannot be predicted from the independent variable.
- If R^{2} is equal to 1, then the dependent variable can be predicted from the independent variable without any error.
- If R^{2} is between 0 and 1, then it indicates the extent that the dependent variable can be predictable. If R^{2 }of 0.10 means, it is 10 percent of the variance in the y variable is predicted from the x variable. If 0.20 means, 20 percent of the variance in the y variable is predicted from the x variable, and so on.
The value of R^{2} shows whether the model would be a good fit for the given data set. In the context of analysis, for any given per cent of the variation, it(good fit) would be different. For instance, in a few fields like rocket science, R^{2} is expected to be nearer to 100 %. But R^{2} = 0(minimum theoretical value), which might not be true as R^{2 } is always greater than 0( by Linear Regression).
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The value of R^{2} increases after adding a new variable predictor. Note that it might not be associated with the result or outcome. The R^{2 } which was adjusted will include the same information as the original one. The number of predictor variables in the model gets penalized. When in a multiple linear regression model, new predictors are added, it would increase R^{2}. Only an increase in R^{2} which is greater than the expected(chance alone), will increase the adjusted R^{2}.
Try Out: Coefficient of Determination Calculator
Following is the Regression line equation
p’ = aq + r
Where ‘p’ is the predicted function value of q. So, the method of checking how good the least-squares equation p̂ = aq + r will make a prediction of how p will be made.
Coefficient of Determination Formula
We can give the formula to find the coefficient of determination in two ways; one using correlation coefficient and the other one with sum of squares.
Formula 1:
As we know the formula of correlation coefficient is,
Where
n = Total number of observations
Σx = Total of the First Variable Value
Σy = Total of the Second Variable Value
Σxy = Sum of the Product of first & Second Value
Σx^{2} = Sum of the Squares of the First Value
Σy^{2} = Sum of the Squares of the Second Value
Thus, the coefficient of of determination = (correlation coefficient)^{2} = r^{2}
Formula 2:
The formula of coefficient of determination is given by:
R^{2} = 1 – (RSS/TSS)
Where,
R^{2} = Coefficient of Determination
RSS = Residuals sum of squares
TSS = Total sum of squares
Properties of Coefficient of Determination
- It helps to get the ratio of how a variable which can be predicted from the other one, varies.
- If we want to check how clear it is to make predictions from the data given, we can determine the same by this measurement.
- It helps to find Explained variation / Total Variation
- It also lets us know the strength of the association(linear) between the variables.
- If the value of r^{2} gets close to 1, The values of y become close to the regression line and similarly if it goes close to 0, the values get away from the regression line.
- It helps in determining the strength of association between different variables.
Steps to Find the Coefficient of Determination
- Find r, Correlation Coefficient
- Square ‘r’.
- Change the above value to a percentage.
Frequently Asked Questions – FAQs
How is R^2 calculated?
R^2 = 1 – (RSS/TSS)
Here,
RSS = Residuals sum of squares
TSS = Total sum of squares
How is the coefficient of determination calculated?
Step 1: Find r, the correlation coefficient
Step 2: Square the value of ‘r’
Step 3: Change the obtained value to a percentage