When would a survival analysis model be used instead of a logistic regression model?

Suppose you a manager for a local car dealership, and you want to use a linear regression model to predict the price of a used car. You decide to use four predictor variables - "Age' (how long the car has been in use since it was produced), "Dents" (the number of visible dents on the outside of the car), "Accidents" (the number of accidents the car has been in), and "mpg" (the fuel efficiency of the car, measured in miles per gallon). Your dataset contains this information for the past 120 cars sold at your dealership. Using this model, your analysis finds an R² of 37%. What is the F statistic of your analysis? Note: 1- Only round your final answer. Round your final answer to two decimal places.

1.How is the slope coefficient (b1) in a simple linear regression different than the coefficient (b1) in a multiple linear regression model? 2. When would you use a logistic regression model?  3.What is the appropriate statistical test to assess whether there is an association between obesity status (normal weight, overweight, obese) and 5-year incident cardiovascular disease (CVD)?  Suppose each participant’s obesity status (category) is known as is whether they develop CVD over the next 5 years or not. *PLEASE INCLUDE TABLE OF THIS

What do you think would be your reservations in relaying on the linear regression model for budgetary planning purposes?