The regression equation, y = 8.5x + 30, is obtained after performing a regression analysis, where x represents the number of hours studied for an exam and y represents the marks on the exam. Is the following statement true or false regarding the analysis above? If the regression square (R^ 2) is 0.949, the number of hours studied is very useful for predicting the exam marks.O TrueO False

It is usefull.

Step-by-step explanation:

The regression squared talks to us about how well the model fits in the experimental data, where 0.0 means that the model does not fit at all, and 100% means that the model fits perfectly.

This is always true? well, really not, there are cases where you can have a regression square of 0.98, which would imply that the model is correct, but when you see the residual vs fit the plot, you may see some pattern, which implies that there is a problem with the model (you always expect to see randomness when you look at this graph). While for a prediction, this actually may work (at least in the range of the data points, outside this range the model and the data may not coincide at all)

Now, it still is useful in a certain range, so we can actually conclude that if R^2 = 0.949 represents a model that is useful for predicting the exam marks.

0.29 bc it’s the last digit and it makes it the lesser value place