Classified ads in the local paper offered several used model A cars for sale. Listed to the right are the ages of the cars and the advertised pricos. Completo parts a through $f$. \begin{tabular}{c|l|c|l|} \multicolumn{2}{c}{} & \multicolumn{2}{r}{ Full data set 은 } \\ \hline Age (yr) & Price Advertised (\$) & Age (yr) & Price Advertised (\$) \\ \hline 1 & $12,975,10,960$ & 6 & 5985,4945 \\ 2 & 10,490 & 9 & $3205,2250,3985$ \\ 3 & $10,975,10,970$ & 11 & 2940,2975 \\ 4 & 6970,7975 & 13 & 1740 \\ 5 & 8710,6965 & & \end{tabular} b) Describe the association between year and price. A. There is a strong negalive linear association between age and price of the model $A$ cars. B. There is a weak positive linear association between age and price of the model A cars. C. There is a weak negative linear association between age and price of the model A cars. D. There is a strong positive linear association between age and price of the model A cars. View an example Get more help - Clear all Check answer
Solution
Step 1 ：Organize the data into two lists: one for the ages of the cars and one for the prices.
Step 2 ：Calculate the correlation coefficient using these lists. The correlation coefficient indicates the strength and direction of the association. A positive correlation coefficient indicates a positive linear association (as age increases, price increases), while a negative correlation coefficient indicates a negative linear association (as age increases, price decreases). A correlation coefficient close to 1 or -1 indicates a strong association, while a correlation coefficient close to 0 indicates a weak association.
Step 3 ：The correlation coefficient is approximately -0.945, which is close to -1. This indicates a strong negative linear association between the age of the cars and their advertised prices. As the age of the car increases, the price decreases.
Step 4 ：Final Answer: \(\boxed{\text{A. There is a strong negative linear association between age and price of the model A cars.}}\)
