# data[].attributes.body
Usually you will get an error. This is because you have to set the window to include the predicted value.

# data[].attributes.body
This is an increasing rate of change, but of course you can have a decreasing rate of change as well as a relation that both increases and decreases its rate of change.

# data[].attributes.body
There are differences between the change in y and the change in the rate of change.

# data[].attributes.body
Same steps as linear regression, but you choose  ExpReg instead of LinReg(ax + b)

# data[].attributes.body
If the first ratios are the "same" then the relation is exponential.
Because of rounding, the ratios may only be close when you do your calculations

# data[].attributes.body
If the first differences are not the same but the second are, then the relation is quadratic.

# data[].attributes.body
Same steps as linear regression, but you choose  QuadReg instead of LinReg(ax + b)

# data[].attributes.body
Get rid of other peoples mistakes.

# data[].attributes.headline
Find the equation of the line of best fit for a scatter plot.

# data[].attributes.subject
Find the equation of the line of best fit for a scatter plot.

# data[].attributes.body
Make Predictions and fix the window

# data[].attributes.body
Enter data and find the equation of the line of best fit.

# data[].attributes.body
Comparing data sets with different shapes.