Below are the scatter plot and residual plot for a set of data. A linear model
(is/is not)

the best fit for the data because the residual plot
(shows no pattern/shows a pattern)

and is
(scattered/not scattered)​

A linear model (is/is not) the best fit for the data because the residual plot (shows no pattern/shows a pattern) and is (scattered/not scattered).

Step-by-step explanation:

A linear model should be used when you want to view the data as a continuous response. This means that when the data is increasing/describing then the line should be in a uniform pattern.

If you were to look at the residual plot, you can see that the points curve in a pattern, meaning that the point is not scattered which is not good criteria for a residual plot.

Mentioned before, the points on the residual plot are in a pattern, so it’s not scattered as well.  

not only in mathematics, scientific proof also are required in the other field of science. also maths proofs are of particular structure, containing steps and logics. so proving is like doing science, it is science. that's why it is important to prove. 

an inaccurate proof leads to errors, or stating results that are not accurate.  which wil mess the probelm up you dont want this

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step-by-step explanation: