Simple regression is used when there is one independent variable. With more independent variables, multiple regression is required.
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it is 75 it that simple
If the regression sum of squares is the explained sum of squares. That is, the sum of squares generated by the regression line. Then you would want the regression sum of squares to be as big as possible since, then the regression line would explain the dispersion of the data well. Alternatively, use the R^2 ratio, which is the ratio of the explained sum of squares to the total sum of squares. (which ranges from 0 to 1) and hence a large number (0.9) would be preferred to (0.2).
yes
Regression, retrograde , retreat .
I believe it is linear regression.