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Regression Modeling: Choosing a Topic and Dataset, Estimating a Model, and Presenting Results


Choose a topic and hypothesis of your choice, find an appropriate dataset, estimate a regression model, and present your model and results in a short essay. Interpret your model in light of the assumptions
you are making when estimating regression models. You can choose any topic or dataset that might interest you. If you need some inspiration, has fascinating long-run datasets,
there is also a list of many datasets already included in R here: , but you are welcome to use any data to answer any question you are interested in (for example: does smoking affect babies’ birthweight? Does
rainfall increase ice cream sales? Has the introduction of airbags/seatbelts lowered car accident deaths?Has the BC carbon tax lowered CO2 emissions? etc.). Present your results in the form of a short written essay (maximum1length of 2 pages + references).

The essay should follow a coherent structure, such as the one suggested below. Sample Structure:
1) Introduction
Stating your hypothesis, explain why this topic is important and interesting and what related literature already exists.
2) Data
Describe your data (including sources and descriptions of variables), perhaps including a
3) Methods
Stating your estimated model (ideally as an equation), justify the functional form you choose (log, etc.) and what assumptions you make.

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