The Defense Advanced Research Projects Agency is interested in contracting you to analyze some data from their air to air missile defense program

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The Defense Advanced Research Projects Agency (DARPA) is interested in contracting you to analyze some data from their air to air missile defense program. When a hostile flying object enters protected airspace, DARPA launches a missile to intercept and destroy that hostile object. Objectively, the missile needs to be able to track the distance between itself and the hostile object accurately. For testing the interceptors, drones were used to simulate hostile flying objects. Drone records provide very accurate information on the location of the drones. The data provided to you includes two variables. First is the actual distance (km) between the missile and the test drone. This is the predictor or explanatory variable. Second is the error (m) in the estimated position of the drone by the missile and the true position of the drone. It should make sense that the farther apart the drone and the missile are, the larger the error will be on average. Your contacts at DARPA have asked that you build a model that can estimate the average error in drone position given a fixed distance between the drone and missile. Your model will then be used to adjust the perceived position of the drone. Specifically, they want to know what you think the average error will be at 0.1, 1 and 10 km respectively. Please provide a short (but thorough) report with your findings. (This is a way over-simplified version of a dataset I actually worked on for DARPA way back in the day...Bonus points if anyone can guess why we see the oscillating behavior in the response variable)

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