Question

the total of squared residuals is called sum of squares of errors

Answer 1

Answer:

Yes you're correct.

Step-by-step explanation:

Please Mark Me As Brainliest.

Answer 2

Correct question:

The total of the squared residuals is called the

A sum of squares Of error

B. coefficient of determination

C.standard error of the estimate

D.coefficient of correlation

The total of the squared residuals is called the A sum of squares Of error

• The residual sum of squares (RSS), sum of squared residuals (SSR), or sum of squared estimate of errors (SSE) are all statistical terms for the sum of the squares of the residuals (deviations predicted from actual empirical values of data).
• This metric quantifies the difference between the data and an estimating model, such as a linear regression.
• A very little RSS indicates a good fit between the model and the data. It acts as a parameter and model selection optimality criterion. Sum of Squares Error, or SSE for short, is also known as residual sum of squares. It is the difference between the projected value and the actual value.
• The final square sum can be zero. The residual sum of squares affects how well your model fits your data; conversely, the bigger the residual sum of squares, the worse your model fits your data. Zero means your model accurately predicted the data.

Hence, the answer is A.

#SPJ2