so believe that personal consumption expenditures might atus (married-single). By setting appropriate dummy variables, construct a regr nsumption but also the marginal propensity to consume a atus. In your regression, you should have the assumption arital status) on autonomous consumption and marginal o categories of marital status (gender). Once you constru rsonal consumption expenditures of each group.

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.

when a regression is used as a method of predicting dependent variables from one or more independent variables. How are the independent variables different from each other yet related to the dependent variable?

In general, what are some problems with using regression to measure causal effects?