Given that the sum of squares for error is 60 and the sum of squares for regression is 140, then the coefficient of determination is:

The coefficient of determination of the dataset is 0.7

The given parameters are:

--- sum of squared error

--- sum of squared regression

Start by calculating the sum of squared total (SST)

This is calculated using

So, we have:

The coefficient of determination (R^2) is then calculated using

So, we have:

Divide

Hence, the coefficient of determination is 0.7

Read more about coefficient of determination at:

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Step-by-step explanation:

The coefficient of determination which is also known as the R² value is expressed as shown;

Sum of square of total (SST)= sum of square of error (SSE )+ sum of square of regression (SSR)

Given SSE = 60 and SSR = 140

SST = 60 + 140

SST = 200

Since R² = SSR/SST

R² = 140/200

R² = 0.7

Hence, the coefficient of determination is 0.7. Note that the coefficient of determination always lies between 0 and 1.

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step-by-step explanation:

an equation by definition has to have two or more variables (x and 2 in this case)