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.

guess at question:

a vertical line intersects the graph of g(x,y) = 0 at two points. what conclusion follows about the function f(x) implicitly defined by g(x,f(x)) = 0?

the domain of f(x) cannot include the x coordinate of any such vertical line.

informally, f(x) is not a function, and

g(x,y)=0 cannot be solved for y uniquely.

the relation r = {(x,y) such that g(x,y) = 0} is a function if

for all (a,b) ∊ r and (c,d) ∊ r, a=c implies b=d.

step-by-step explanation: