Imagine that you have plotted many data points on an xy-plane. Your points seem to align into a clear best-fit line. Do you think this best-fit line can help you make predictions about future data? Explain your answer, and give one or more examples to support it.

A best-fit line shows an association between two variables and can therefore be used to make predictions.

An example is a scatterplot attached below showing a best-fit line that depicts the association between the number of people that bath in a pool and daily temperature.

(see attachment below).

Recall:

Therefore, a best-fit line shows an association between two variables and can therefore be used to make predictions.

An example is a scatterplot attached below showing a best-fit line that depicts the association between the number of people that bath in a pool and daily temperature.

(see attachment below).

Learn more here:

link

It depends really. If you stay close to the present, then predicting future results isn't too bad. The further you go out, the more unpredictable things get. This is because the points may deviate from the line of best fit (aka regression line) as time wears on. Of course, it also depends on what kind of data we're working with. Some pairs of variables are naturally going to correlate very strongly together. An example would be temperature versus ice cream sales.

the solution is 12x-6y

sorry can't

step-by-step explanation:

i googled though and something came up but it was in science langueage not common english sooo