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The cost and customer rating of 15 cars is shown on the scatterplot. The cars are rated on a scale of 0 to 100. Scatterplot with x axis labeled Car Price, US dollars, going from 2,000 to 5,000 and y axis labeled Rating going from 0 to 120. Values at 2,678, 33; 2,774, 40; 2,961, 30; 2,945, 15; 3,356, 44; 3,335, 66; 3,489, 98; ,3613, 86; 3,906, 49; 3,997, 55; 4,030, 65; 4,200, 11; 4,350, 54; 4,494, 75; 4,601, 74. Part A: Describe the association shown in the scatterplot. (4 points). Part B: Give an example of a data point that affects the appropriateness of using a linear regression model to fit all the data. Explain. (4 points) Part C: Give an example of a car that is cost effective and rated highly by customers. (2 points)

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Based on the scatter plot for this data, we can logically deduce that the association between them is a positive association.

What is a scatter plot?

A scatter plot can be defined as a type of graph which is used to graphically represent the values of two (2) variables, with the resulting points showing any association (correlation) between the data set.

Part A.

Based on the scatter plot for this data, we can deduce that the association between them is a positive association because the price and customer rating increases together.

Part B.

An example of a data point which would affect the appropriateness of using a linear regression model to fit all the data is car price of $4,601 and customer rating of 100. Part C. An example of a car that is cost effective and rated highly by customers is the one with a customer rating of 100 and sold at$3,500.

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