STATISTICAL TECHNIQUES AND TOOLS
CORRELATION COEFFICIENT COEFFICIENT OF DETERMINATION
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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The number of pickles on your hamburger.
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The answer to the question being asked.
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The percentage of data that is on the Line of Best Fit.
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The equation of the line of best fit.
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Detailed explanation-1: -The coefficient of determination (R²) measures how well a statistical model predicts an outcome. The outcome is represented by the model’s dependent variable. The lowest possible value of R² is 0 and the highest possible value is 1.
Detailed explanation-2: -In regression, the R2 coefficient of determination is a statistical measure of how well the regression predictions approximate the real data points. An R2 of 1 indicates that the regression predictions perfectly fit the data.
Detailed explanation-3: -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.
Detailed explanation-4: -The coefficient of determination, r2, is equal to the square of the correlation coefficient. When expressed as a percent, the coefficient of determination represents the percent of variation in the dependent variable y that can be explained by the variation in the independent variable x using the regression line.