Answer:
Step-by-step explanation:
The coefficient of determination which is also known as the R² value is expressed as shown;
[tex]R^{2} = \frac{sum\ of \ squares \ of \ regression}{sum\ of \ squares \ of total}[/tex]
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.
The coefficient of determination of the dataset is 0.7
The given parameters are:
[tex]SSE = 60[/tex] --- sum of squared error
[tex]SSR = 140[/tex] --- sum of squared regression
Start by calculating the sum of squared total (SST)
This is calculated using
[tex]SST =SSE + SSR[/tex]
So, we have:
[tex]SST =60 +140[/tex]
[tex]SST =200[/tex]
The coefficient of determination (R^2) is then calculated using
[tex]R^2 = \frac{SSR}{SST}[/tex]
So, we have:
[tex]R^2 = \frac{140}{200}[/tex]
Divide
[tex]R^2 = 0.7[/tex]
Hence, the coefficient of determination is 0.7
Read more about coefficient of determination at:
https://brainly.com/question/15804563
