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Q: Which type of graph is most useful for making predictions about the dependent variable?

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line graph

Not useful

i need a answer!!

When you want the central location of a variable.

It gives a measure of the extent to which values of the dependent variable move with values of the independent variables. This will enable you to decide whether or not the model has any useful predictive properties (significance). It also gives a measure of the expected changes in the value of the dependent variable which would accompany changes in the independent variable. A regression model cannot offer an explanation. The fact that two variables move together does not mean that changes in one cause changes in the other. Furthermore it is possible to have very closely related variables which, because of a wrongly specified model, can show no correlation. For example, a LINEAR model fitted to y=x2 over a symmetric range for x will show zero correlation!

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i believe the answer is.... A strong OBSERVATION can be useful for making predictions

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function is the relationship between independent variable & dependent variable i.e. F:R-R

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A line graph is most useful for representing how one variable influences another variable.

The variable of the experiment that is being tested or the part that is changed by the person doing the experiment is called the independent variable... Thank you for letting me answer goodbye... ;)