A small technology company started offering shares of stock to investors in 1987. At that time, the price of one share of stock was $0.39. Since then, the company has experienced rapid growth. Twenty-two years later, the price of a single share of stock has risen to over $110. One scatterplot shown summarizes the number of years since the initial stock offering in 1987 and the price of the stock, while the other compares years since 1987 to the log of stock price. A graph titled growth in stock price has years since 1987 on the x-axis, and stock price (dollars) on the y-axis. The points curve up exponentially. A graph titled growth in stock price has years since 1987 on the x-axis, and log (stock price) on the y-axis. The points increase in a line with positive slope. Based on these scatterplots, what type of model is most appropriate for summarizing the relationship between year and stock price? A linear model is appropriate because the scatterplot of the transformed data is roughly linear. An exponential model is appropriate because the scatterplot of time and log price is increasing. An exponential model could be appropriate because the scatterplot of log height versus log weight is roughly linear. The next step is to look at the residual plot. A power model is appropriate because the scatterplot of time and price shows a curved relationship.