Finding Coefficient of Determination

In summary, the coefficient of determination, also known as R-squared, is a statistical measure that represents the proportion of the variance in the dependent variable that is explained by the independent variable(s). It is calculated by squaring the Pearson correlation coefficient, resulting in a value between 0 and 1. A high coefficient of determination indicates a strong relationship between the variables, while a low coefficient of determination indicates a weak relationship. It cannot be negative and should be interpreted in conjunction with the p-value to determine the significance of the relationship.
  • #1
Tchao
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Homework Statement



If the slope of the regression line is negative and the correlation coefficient is -0.5, coefficient of determination is:

Homework Equations



coefficient of determination: r2 = 1 - SSE/SST

correlation coefficient: r = Sxy / (√Sxx * √Syy )

The Attempt at a Solution


r = -0.5
r2 = 0.25 but because slope of regression line is negative, then coefficient of determination would be also negative.
r2 = -0.25

I am not sure if my though process in determining the correct answer is right or not.
 

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  • #2
Tchao said:

Homework Statement



If the slope of the regression line is negative and the correlation coefficient is -0.5, coefficient of determination is:

Homework Equations



coefficient of determination: r2 = 1 - SSE/SST

correlation coefficient: r = Sxy / (√Sxx * √Syy )

The Attempt at a Solution


r = -0.5
r2 = 0.25 but because slope of regression line is negative, then coefficient of determination would be also negative.
r2 = -0.25

I am not sure if my though process in determining the correct answer is right or not.

Hi Tchao,

Indeed, the coefficient of determination is ##r^2=0.25##.
And it is positive, since a square is always positive.
It means that the coefficient of determination doesn't tell us whether the slope is upward or downward, only that there is a correlation.
 
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Likes Greg Bernhardt

1. What is the coefficient of determination?

The coefficient of determination, also known as R-squared, is a statistical measure that represents the proportion of the variance in the dependent variable that is explained by the independent variable(s). It is a value between 0 and 1, with higher values indicating a stronger relationship between the variables.

2. How is the coefficient of determination calculated?

The coefficient of determination is calculated by squaring the Pearson correlation coefficient, which measures the strength and direction of the linear relationship between two variables. This calculation results in a value between 0 and 1, with 0 indicating no relationship and 1 indicating a perfect relationship.

3. What does a high or low coefficient of determination indicate?

A high coefficient of determination (close to 1) indicates that a large proportion of the variance in the dependent variable is explained by the independent variable(s), and therefore the model is a good fit for the data. A low coefficient of determination (close to 0) indicates that the independent variable(s) have little or no impact on the dependent variable, and the model is a poor fit for the data.

4. Can the coefficient of determination be negative?

No, the coefficient of determination cannot be negative. It is always a value between 0 and 1. A negative value would indicate a negative relationship between the variables, which is not possible in linear regression.

5. How do you interpret the coefficient of determination?

The coefficient of determination should be interpreted in conjunction with the p-value, which indicates the statistical significance of the relationship. Generally, a higher coefficient of determination and a lower p-value indicate a stronger and more significant relationship between the variables. However, it is important to also consider the context and the specific research question when interpreting the coefficient of determination.

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