Respuesta :
The value of the sum of squares due to regression is 18.43.
Given the total sum of squares (SST) is 25.32 and the sum of squares due to error (SSE) is 6.89.
A common measure used in regression analysis is the sum of squares total (SST). The square of each difference is added to the sum of squares to obtain the squared disparities between individual data points and their mean. The variance is calculated using the sum of squares, which is also used to assess how well a regression curve fits the data.
We will use the total sum of squares (SST) is given as the summation of the sum of squares due to regression (SSR) and sum of squares error (SSE);
SST = SSR + SSE
Here, SST=25.32 and SSE=6.89
Substitute the values in the formula, we get
25.32=SSR+6.89
Now, we will subtract 6.89 from both sides, we get
25.32-6.89=SSR+6.89-6.89
18.43=SSR
Hence, the value of the sum of squares due to regression (SSR) when the total sum of squares (SST) is 25.32 and the sum of squares due to error (SSE) is 6.89 is 18.43.
Learn more about regression from here brainly.com/question/23438254
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