Scatterplot of Road-Test Score vs Price ($1000) 100 90 80 Road-Test Score 70 50 50 15 20 25 30 35 40 Price ($1000) SUMMARY OUTPUT Regression Statistics Multiple R 0.457966 R Square 0.209733 Adjusted F 0.194535 Standard E 8.109873 Observatic 54 Coefficientandard Err t Stat P-value Intercept 61.14899 4.687752 13.04442 5.01E-18 Price($10( 0.59721 0.16076For 54 cars in model year 2022, researchers for a consumer group record the Price ($1000) and a Road Test Score (RTS) given by a professional driver. Using Excel, they fit the simple regression model, RTS vs. Price ($1000). Above is a scatterplot of the model and some of the regression output from Excel (with some deletions). Use the above to answer this question. Assume valid normal linear model conditions. The 2022 Chevy Malibu, not one of the cars in the dataset, has a price of $28,000. Based on this model, which of the choices below is/are true? I. The Chevy Malibu will be predicted to have an RTS of 77.87. Il. The Chevy Malibu will have an RTS of 77.87. Ill. The predicted RTS of the Chevy Malibu will be greater than its actual RTS. IV. The predicted RTS of the Chevy Malibu will be less than its actual RTS