1. You collected data from a random sample of cities to see what factors are associated with cost of living (COL, measured using an index where 100 is the average cost of living for US cities). The independent variables you chose are average monthly rent cost (in $) and average bus ride cost (in $). Use the accompanying regression table to answer the following questions.

Coefficients Standard Error

Intercept 46.15 20.92

Rent cost 0.02 0.0056

Bus cost 5.83 2.77

Interpret the coefficient on Bus cost.

A. After accounting for rent, a one unit decrease in COL is associated with a 5.83 increase in bus fares.

B. After accounting for rent, a one dollar decrease in bus fares is associated with a COL increase of 5.83

C. After accounting for rent, a one unit increase in COL is associated with a 5.83 increase in bus fares.

D. After accounting for rent, a one dollar increase in bus fares is associated with a COL increase of 5.83

E. A one dollar increase in bus fares is associated with a COL decrease of 5.83 9.

2. After seeing the regression output from above, a concerned citizen claimed the output proved that if the city he lived in enacted rent controls, prohibiting apartments from charging more than $1700/month in rent, it would lower the city's cost of living. Evaluate the citizen's claim.

A. The citizen's claim is true

B. The citizen claims that changing rent costs would cause the cost of living to change. The regression output does not prove a causal relationship exists. C. The citizen's claim is false. The rent control would have to be lower than $1700/month to ensure that cost of living decreased.

D. The citizen's claim is false. The rent control would only lower cost of living if we hold the cost of bus fares constant. E. The citizen's claim is false. The city would have to increase monthly rents to lower the cost of living.